16.7.4.2.7 Counting People, Transportation System Monitoring, Queues

Chapter Contents (Back)
Human Detection. Counting People. See also Human Detection, People Detection, Pedestrians, Locating. See also Tracking People, Human Tracking, Pedestrian Tracking.

Reveal,
2000. Pedestrian Counting Systems.
WWW Link. Vendor, Pedestrian Tracking. Vendor, Surveillance.

Seki, H.[Hiroshi],
Method and apparatus for detecting the number of persons,
US_Patent5,121,201, Jun 9, 1992
WWW Link. BibRef 9206

Suzuki, M.[Masato], Inaba, H.[Hiromi], Nakamura, K.[Kiyoshi], Nakata, N.[Naofumi], Yamani, H.[Hiroaki], Oonuma, N.[Naoto],
Apparatus and methods for detecting number of people waiting in an elevator hall using plural image processing means with overlapping fields of view,
US_Patent5,298,697, Mar 29, 1994
WWW Link. BibRef 9403

Suzuki, M.[Masato], Inaba, H.[Hiromi], Takenaga, H.[Hiroshi], Yamazaki, M.[Masachika], Oonuma, N.[Naoto], Nakamura, N.[Niyoshi], Sakai, Y.[Yoshio], Yoneda, K.[Kenji], Nakata, N.[Naofumi], Kasai, S.[Syoji],
Image processing apparatus having apparatus for correcting the image processing,
US_Patent5,182,776, Jan 26, 1993
WWW Link. Count people in elevator by background difference. BibRef 9301

Bartolini, F., Cappellini, V., Mecocci, A.,
Counting People Getting in and out of a Bus by Real-Time Image-Sequence Processing,
IVC(12), No. 1, January-February 1994, pp. 36-41.
Elsevier DOI BibRef 9401

Mecocci, A., Bartolini, F., Cappellini, V.,
Image Sequence Analysis for Counting in Real Time People Getting in and out of a Bus,
SP(35), No. 2, 1994, pp. 105-116. BibRef 9400

Schofield, A.J., Mehta, P.A., Stonham, T.J.,
A System for Counting People in Video Images Using Neural Networks to Identify the Background Scene,
PR(29), No. 8, August 1996, pp. 1421-1428.
Elsevier DOI 9608
BibRef

Khoudour, L., Duvieubourg, L., Deparis, J.P.,
Real-Time Pedestrian Counting by Active Linear Cameras,
JEI(5), No. 4, October 1996, pp. 452-459. 9709
BibRef

Huang, J.Z.[Jian-Zhong], Florencio, D.A.F.[Dinei A.F.],
System and method for detecting and analyzing a queue,
US_Patent5,953,055, Sep 14, 1999
WWW Link. BibRef 9909
And: US_Patent6,195,121, Feb 27, 2001
WWW Link. BibRef

Iketani, A.[Akihiko], Nagai, A.[Atsushi], Kuno, Y.[Yoshinori], Shirai, Y.[Yoshiaki],
Real-Time Surveillance System Detecting Persons in Complex Scenes,
RealTimeImg(7), No. 5, October 2001, pp. 433-446.
DOI Link 0110
BibRef
Earlier:
Detecting Persons on Changing Background,
ICPR98(Vol I: 74-76).
IEEE DOI 9808
BibRef
Earlier: A1, A3, Add Shimada, N., A4 Only: CIAP99(1112-1115).
IEEE DOI 9909
BibRef

Nagai, A., Kuno, Y., Shirai, Y.,
Surveillance system based on spatio-temporal information,
ICIP96(II: 593-596).
IEEE DOI 9610
BibRef

Sacchi, C.[Claudio], Gera, G.[Gianluca], Marcenaro, L.[Lucio], Regazzoni, C.S.[Carlo S.],
Advanced image-processing tools for counting people in tourist site-monitoring applications,
SP(81), No. 5, May 2001, pp. 1017-1040.
HTML Version. 0105
BibRef

Mazzu, A.[Andrea], Chiappino, S.[Simone], Marcenaro, L.[Lucio], Regazzoni, C.S.[Carlo S.],
A track-before-detect algorithm using joint probabilistic data association filter and interacting multiple models,
ICIP14(4947-4951)
IEEE DOI 1502
BibRef
Earlier: A2, A3, A4, Only:
Selective attention automatic focus for cognitive crowd monitoring,
AVSS13(13-18)
IEEE DOI 1311
Covariance matrices video surveillance BibRef

Albiol, A., Mora, I., Naranjo, V.,
Real-time High Density People Counter Using Morphological Tools,
ITS(2), No. 4, December 2001, pp. 204-218.
IEEE Abstract. 0402
BibRef
Earlier: A1, A3, A2: ICPR00(Vol IV: 652-655).
IEEE DOI 0009
BibRef

Albiol, A.[Antonio], Albiol, A.[Alberto], Silla, J.[Julia],
Statistical video analysis for crowds counting,
ICIP09(2569-2572).
IEEE DOI 0911
BibRef

Lin, S.F.[Sheng-Fuu], Chen, J.Y.[Jaw-Yeh], Chao, H.X.[Hung-Xin],
Estimation of number of people in crowded scenes using perspective transformation,
SMC-A(31), No. 6, November 2001, pp. 645-654.
IEEE Top Reference. 0202
BibRef

Seow, K.T.[Kiam Tian], Pasquier, M.,
Supervising passenger land-transport systems,
ITS(5), No. 3, September 2004, pp. 165-176.
IEEE Abstract. 0501
BibRef

Pai, C.J.[Chia-Jung], Tyan, H.R.[Hsiao-Rong], Liang, Y.M.[Yu-Ming], Liao, H.Y.M.[Hong-Yuan Mark], Chen, S.W.[Sei-Wang],
Pedestrian detection and tracking at crossroads,
PR(37), No. 5, May 2004, pp. 1025-1034.
Elsevier DOI 0405
BibRef
Earlier: ICIP03(II: 101-104).
IEEE DOI 0312
BibRef

Chen, D.Y.[Duan-Yu], Cannons, K., Tyan, H.R.[Hsiao-Rong], Shih, S.W.[Sheng-Wen], Liao, H.Y.M.,
Spatiotemporal Motion Analysis for the Detection and Classification of Moving Targets,
MultMed(10), No. 8, December 2008, pp. 1578-1591.
IEEE DOI 0905
BibRef

Su, C.W.[Chih-Wen], Liao, H.Y.M.[Hong-Yuan Mark], Liang, Y.M.[Yu-Ming], Tyan, H.R.[Hsiao-Rong],
An RST-Tolerant Shape Descriptor for Object Detection,
ICPR10(766-769).
IEEE DOI 1008
Rotation, Scale, Translation. BibRef

Hsieh, J.W.[Jun-Wei], Hsu, Y.T.[Yung-Tai], Liao, H.Y.M., Chen, C.C.A.[Chih-Chi-Ang],
Video-Based Human Movement Analysis and Its Application to Surveillance Systems,
MultMed(10), No. 3, April 2008, pp. 372-384.
IEEE DOI 0905
BibRef

Munder, S., Gavrila, D.M.[Dariu M.],
An Experimental Study on Pedestrian Classification,
PAMI(28), No. 11, November 2006, pp. 1863-1868.
IEEE DOI
PDF File. 0609
Dataset available:
HTML Version. Dataset, Pedestrians. DaimlerChrysler Res. Investigate global versus local and adaptive versus nonadaptive features. PCA coefficients, Haar wavelets, and local receptive fields (LRFs). SVM, Neural Nets, K-NN classifiers. Combination of SVMs with LRF features performs best. And boosted cascade of Haar wavelets is close. BibRef

Mählisch, M., Oberländer, M., Löhlein, O., Gavrila, D.M., and Ritter, W.,
A Multiple Detector Approach to Low-Resolution FIR Pedestrian Recognition,
IVS05(xx-yy).
PDF File. BibRef 0500

Gavrila, D.M.[Dariu M.], Giebel, J., Munder, S.,
Vision-based pedestrian detection: the PROTECTOR system,
IVS04(13-18).
WWW Link. 0411
Although promising, not yet ready for prime time. BibRef

Gavrila, D.M.,
Looking at people,
AVSBS07(1-1).
IEEE DOI 0709
BibRef

Munder, S., Schnorr, C., Gavrila, D.M.,
Pedestrian Detection and Tracking Using a Mixture of View-Based Shape-Texture Models,
ITS(9), No. 2, June 2008, pp. 333-343.
IEEE DOI 0806
BibRef

Giebel, J., Gavrila, D.M., Schnörr, C.,
A Bayesian Framework for Multi-cue 3D Object Tracking,
ECCV04(Vol IV: 241-252).
Springer DOI
PDF File. 0405
Integrate object detection. Apply to pedestrians. BibRef

Gavrila, D.M.[Dariu M.],
Sensor-based Pedestrian Protection,
IEEE_Int_Sys(16), No. 6, 2001, pp. 77-81.
PDF File. BibRef 0100
Earlier:
Pedestrian Detection from a Moving Vehicle,
ECCV00(II: 37-49).
Springer DOI 0003
BibRef

Gavrila, D.M., Munder, S.,
Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle,
IJCV(73), No. 1, June 2007, pp. 41-59.
Springer DOI 0702
BibRef

Gavrila, D.M.[Dariu M.], Philomin, V.,
Real-Time Object Detection for Smart Vehicles,
ICCV99(87-93).
IEEE DOI
PDF File. BibRef 9900

Heikkilä, J.[Janne], Silvén, O.[Olli],
A Real-Time System for Monitoring of Cyclists and Pedestrians,
IVC(22), No. 7, July 2004, pp. 563-570.
Elsevier DOI 0405
BibRef
Earlier: VS99(xx-yy). BibRef

Heikkila, J.[Janne], Silven, O.[Olli],
Linear Motion Estimation for Image Sequence Based Accurate 3-D Measurements,
ICPR98(Vol II: 1247-1250).
IEEE DOI 9808
BibRef

Ling, H.[Huang], Wu, J.P.[Jian-Ping],
A study on cyclist behavior at signalized intersections,
ITS(5), No. 4, December 2004, pp. 293-299.
IEEE Abstract. 0501
BibRef

Bird, N.D., Masoud, O.T., Papanikolopoulos, N.P., Isaacs, A.,
Detection of Loitering Individuals in Public Transportation Areas,
ITS(6), No. 2, June 2005, pp. 167-177.
IEEE Abstract. 0506
BibRef

Velastin, S.A., Boghossian, B., Lo, B., Sun, J., Vicencio-Silva, M.A.,
PRISMATICA: Toward Ambient Intelligence in Public Transport Environments,
SMC-A(35), No. 1, January 2005, pp. 164-182.
IEEE Abstract. 0501
BibRef

Black, J., Velastin, S.A.[Sergio A.], Boghossian, B.[Boghos],
A real time surveillance system for metropolitan railways,
AVSBS05(189-194).
IEEE DOI 0602
BibRef

Nair, V.[Vinod], Laprise, P.O.[Pierre-Olivier], Clark, J.J.[James J.],
An FPGA-Based People Detection System,
JASP(2005), No. 7, 2005, pp. 1047-1061.
WWW Link. 0603
BibRef

Casas, J.R., Sitjes, A.P., Folch, P.P.,
Mutual feedback scheme for face detection and tracking aimed at density estimation in demonstrations,
VISP(152), No. 3, June 2005, pp. 334-346.
DOI Link 0510
BibRef

Marcenaro, L., Marchesotti, L., Regazzoni, C.S.,
Self-organizing shape description for tracking and classifying multiple interacting objects,
IVC(24), No. 11, 1 November 2006, pp. 1179-1191.
Elsevier DOI 0610
BibRef
Earlier:
Tracking and Counting Multiple Interacting People in Indoor Scenes,
PETS02(56-61). 0207
BibRef

Morerio, P.[Pietro], Marcenaro, L.[Lucio], Regazzoni, C.S.[Carlo S.],
People Count Estimation In Small Crowds,
AVSS12(476-480).
IEEE DOI 1211
BibRef

Marchesotti, L., Piva, S., Regazzoni, C.S.,
An agent-based approach for tracking people in indoor complex environments,
CIAP03(99-102).
IEEE DOI 0310
BibRef

Antonini, G.[Gianluca], Martinez, S.V.[Santiago Venegas], Bierlaire, M.[Michel], Thiran, J.P.[Jean Philippe],
Behavioral Priors for Detection and Tracking of Pedestrians in Video Sequences,
IJCV(69), No. 2, August 2006, pp. 159-180.
Springer DOI 0606
BibRef
Earlier: A2, A1, A4, A3:
Bayesian integration of a discrete choice pedestrian behavioral model and image correlation techniques for automatic multi object tracking,
ICIP04(II: 1037-1040).
IEEE DOI 0505
BibRef

Alahi, A.[Alexandre], Marimon, D.[David], Bierlaire, M.[Michel], Kunt, M.[Murat],
A master-slave approach for object detection and matching with fixed and mobile cameras,
ICIP08(1712-1715).
IEEE DOI 0810
BibRef
Earlier: A1, A3, A4, Only:
Object Detection and Matching with Mobile Cameras Collaborating with Fixed Cameras,
M2SFA208(xx-yy). 0810
Primarily for pedestrians. BibRef

Alahi, A.[Alexandre], Vandergheynst, P.[Pierre], Bierlaire, M.[Michel], Kunt, M.[Murat],
Cascade of descriptors to detect and track objects across any network of cameras,
CVIU(114), No. 6, June 2010, pp. 624-640.
Elsevier DOI 1006
Object detection; Object tracking; Region descriptors; Cascade of descriptors; Multi-view; Mobile cameras; Pedestrian recognition BibRef

Alahi, A.[Alexandre], Jacques, L.[Laurent], Boursier, Y.[Yannick], Vandergheynst, P.[Pierre],
Sparsity Driven People Localization with a Heterogeneous Network of Cameras,
JMIV(41), No. 1-2, September 2011, pp. 39-58.
WWW Link. 1108
BibRef
Earlier:
Sparsity-driven people localization algorithm: Evaluation in crowded scenes environments,
PETS-Winter09(1-8).
IEEE DOI 0912
BibRef

Biliotti, D.[David], Antonini, G.[Gianluca], Thiran, J.P.[Jean Philippe],
Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences,
Motion05(II: 50-57).
IEEE DOI 0502
BibRef

Antonini, G.[Gianluca], Thiran, J.P.[Jean Philippe],
Counting Pedestrians in Video Sequences Using Trajectory Clustering,
CirSysVideo(16), No. 8, August 2006, pp. 1008-1020.
IEEE DOI 0609
BibRef

Ramaswamy, A.[Arun], Nelson, D.J.[Daniel J.], Srinivasan, V.[Venugopal],
Methods and apparatus to count people appearing in an image,
US_Patent7,203,338, Apr 10, 2007
WWW Link. BibRef 0704

Kilambi, P.[Prahlad], Ribnick, E.[Evan], Joshi, A.J.[Ajay J.], Masoud, O.T.[Osama T.], Papanikolopoulos, N.P.[Nikolaos P.],
Estimating pedestrian counts in groups,
CVIU(110), No. 1, April 2008, pp. 43-59.
Elsevier DOI 0804
Groups; Count estimation; Pedestrian tracking; Occlusions; Projection BibRef

Ribnick, E.[Evan], Atev, S.[Stefan], Papanikolopoulos, N.P.[Nikolaos P.],
Estimating 3D Positions and Velocities of Projectiles from Monocular Views,
PAMI(31), No. 5, May 2009, pp. 938-944.
IEEE DOI 0903
BibRef
Earlier: A1, A3, Only:
Estimating 3D Trajectories of Periodic Motions from Stationary Monocular Views,
ECCV08(III: 546-559).
Springer DOI 0810
Localization based on apparent motion in monocular view. BibRef

Ribnick, E.[Evan], Sivalingam, R.[Ravishankar], Papanikolopoulos, N.[Nikolaos], Daniilidis, K.[Kostas],
Reconstructing and analyzing periodic human motion from stationary monocular views,
CVIU(116), No. 7, July 2012, pp. 815-826.
Elsevier DOI 1202
Human motion; 3D reconstruction; Periodicity; Activity classification; Gait analysis BibRef

Sidla, O.[Oliver],
Improved pedestrian tracking for urban planning,
SPIE(Newsroom), December 17, 2009.
DOI Link 0912
Enhanced image-analysis methods enable new applications for public-transport scheduling, traffic control, and safety monitoring. BibRef

Xu, S., Duh, H.B.L.,
A Simulation of Bonding Effects and Their Impacts on Pedestrian Dynamics,
ITS(11), No. 1, March 2010, pp. 153-161.
IEEE DOI 1003
BibRef

Gerónimo, D.[David], Sappa, A.D.[Angel D.], Ponsa, D.[Daniel], López, A.M.[Antonio M.],
2D-3D-based on-board pedestrian detection system,
CVIU(114), No. 5, May 2010, pp. 583-595.
Elsevier DOI 1004
BibRef
Earlier: A1, A4, A3, A2:
Haar Wavelets and Edge Orientation Histograms for On-Board Pedestrian Detection,
IbPRIA07(I: 418-425).
Springer DOI 0706
Pedestrian detection; Advanced Driver Assistance Systems; Horizon line; Haar wavelets; Edge orientation histograms BibRef

Gerónimo, D.[David], López, A.M.[Antonio M.], Sappa, A.D.[Angel D.],
Computer Vision Approaches to Pedestrian Detection: Visible Spectrum Survey,
IbPRIA07(I: 547-554).
Springer DOI 0706
BibRef

Geronimo, D.[David], Lopez, A.M.[Antonio M.], Sappa, A.D.[Angel D.], Graf, T.[Thorsten],
Survey of Pedestrian Detection for Advanced Driver Assistance Systems,
PAMI(32), No. 7, July 2010, pp. 1239-1258.
IEEE DOI 1006
Survey, Pedestrian Detection. Driver Assistance. How to deal with the variations in appearance of pedestrians. BibRef

Marin, J.[Javier], Vazquez, D.[David], Geronimo, D.[David], Lopez, A.M.[Antonio M.],
Learning appearance in virtual scenarios for pedestrian detection,
CVPR10(137-144).
IEEE DOI 1006
BibRef

Hou, Y.L., Pang, G.K.H.,
People Counting and Human Detection in a Challenging Situation,
SMC-A(41), No. 1, January 2011, pp. 24-33.
IEEE DOI 1011
BibRef

Tan, B.[Ben], Zhang, J.P.[Jun-Ping], Wang, L.[Liang],
Semi-supervised Elastic net for pedestrian counting,
PR(44), No. 10-11, October-November 2011, pp. 2297-2304.
Elsevier DOI 1101
Semi-supervised regression; Elastic net; Pedestrian counting; Feature selection; Statistical landscape features BibRef

Fernandez Llorca, D., Milanes, V., Parra Alonso, I., Gavilan, M., Garcia Daza, I., Perez, J., Sotelo, M.Á.,
Autonomous Pedestrian Collision Avoidance Using a Fuzzy Steering Controller,
ITS(12), No. 2, June 2011, pp. 390-401.
IEEE DOI 1101
BibRef

Yuan, X.[Xue], Wei, X.Y.[Xue-Ye], Song, Y.D.[Yong-Duan],
Pedestrian Detection for Counting Applications Using a Top-View Camera,
IEICE(E94-D), No. 6, June 2011, pp. 1269-1277.
WWW Link. 1101
BibRef

Lee, G.G.[Gwang-Gook], Kim, W.Y.[Whoi-Yul],
A Statistical Method for Counting Pedestrians in Crowded Environments,
IEICE(E94-D), No. 6, June 2011, pp. 1357-1361.
WWW Link. 1101
BibRef

Chen, Z.[Zhuo], Wang, L.[Lu], Yung, N.H.C.[Nelson H.C.],
Adaptive human motion analysis and prediction,
PR(44), No. 12, December 2011, pp. 2902-2914.
Elsevier DOI 1107
Motion pattern; Pattern clustering; Pattern classification; Prediction BibRef

Wang, L.[Lu], Yung, N.H.C.[Nelson H.C.],
Three-Dimensional Model-Based Human Detection in Crowded Scenes,
ITS(13), No. 2, June 2012, pp. 691-703.
IEEE DOI 1206
BibRef
Earlier:
Bayesian 3D model based human detection in crowded scenes using efficient optimization,
WACV11(557-563).
IEEE DOI 1101
BibRef
Earlier:
Crowd counting and segmentation in visual surveillance,
ICIP09(2573-2576).
IEEE DOI 0911
BibRef

Keller, C.G., Dang, T., Fritz, H., Joos, A., Rabe, C., Gavrila, D.M.,
Active Pedestrian Safety by Automatic Braking and Evasive Steering,
ITS(12), No. 4, December 2011, pp. 1292-1304.
IEEE DOI 1112
BibRef

Zhang, J., Tan, B., Sha, F., He, L.,
Predicting Pedestrian Counts in Crowded Scenes With Rich and High-Dimensional Features,
ITS(12), No. 4, December 2011, pp. 1037-1046.
IEEE DOI 1112
BibRef

Ge, W.[Weina], Collins, R.T.[Robert T.], Ruback, R.B.[R. Barry],
Vision-Based Analysis of Small Groups in Pedestrian Crowds,
PAMI(34), No. 5, May 2012, pp. 1003-1016.
IEEE DOI 1204
BibRef
Earlier:
Automatically detecting the small group structure of a crowd,
WACV09(1-8).
IEEE DOI 0912
Not just single pedestrians, but small groups traveling together. Clustered by proxmimity and velocity. BibRef

Ge, W.[Weina], Collins, R.T.[Robert T.],
Crowd Detection with a Multiview Sampler,
ECCV10(V: 324-337).
Springer DOI 1009
BibRef
Earlier:
Evaluation of sampling-based pedestrian detection for crowd counting,
PETS-Winter09(1-7).
IEEE DOI 0912
Evaluation, Human Detection. BibRef
Earlier:
Marked point processes for crowd counting,
CVPR09(2913-2920).
IEEE DOI 0906
BibRef

Chan, A.B.[Antoni B.], Vasconcelos, N.M.[Nuno M.],
Counting People With Low-Level Features and Bayesian Regression,
IP(21), No. 4, April 2012, pp. 2160-2177.
IEEE DOI 1204
BibRef
Earlier:
Bayesian Poisson regression for crowd counting,
ICCV09(545-551).
IEEE DOI 0909
BibRef

Liu, B., Vasconcelos, N.M.,
Bayesian Model Adaptation for Crowd Counts,
ICCV15(4175-4183)
IEEE DOI 1602
Adaptation models BibRef

Damen, D.[Dima], Hogg, D.C.[David C.],
Explaining Activities as Consistent Groups of Events: A Bayesian Framework Using Attribute Multiset Grammars,
IJCV(98), No. 1, May 2012, pp. 83-102.
WWW Link. 1204
BibRef
Earlier:
Attribute Multiset Grammars for Global Explanations of Activities,
BMVC09(xx-yy).
PDF File. 0909
BibRef
And:
Recognizing linked events: Searching the space of feasible explanations,
CVPR09(927-934).
IEEE DOI 0906
See also Detecting Carried Objects from Sequences of Walking Pedestrians. BibRef

Hung, D.H.[Dao-Huu], Hsu, G.S.[Gee-Sern], Chung, S.L.[Sheng-Luen], Saito, H.[Hideo],
Real-Time Counting People in Crowded Areas by Using Local Empirical Templates and Density Ratios,
IEICE(E95-D), No. 7, July 2012, pp. 1791-1803.
WWW Link. 1208
BibRef
Earlier: A1, A3, A2, Only:
Local Empirical Templates and Density Ratios for People Counting,
ACCV10(IV: 90-101).
Springer DOI 1011
BibRef

Garcia-Bunster, G., Torres-Torriti, M., Oberli, C.,
Crowded pedestrian counting at bus stops from perspective transformations of foreground areas,
IET-CV(6), No. 4, 2012, pp. 296-305.
DOI Link 1209
See also Performance Evaluation of UHF RFID Technologies for Real-Time Passenger Recognition in Intelligent Public Transportation Systems. BibRef

Xu, Y., Xu, D., Lin, S., Han, T.X., Cao, X., Li, X.,
Detection of Sudden Pedestrian Crossings for Driving Assistance Systems,
SMC-B(42), No. 3, June 2012, pp. 729-739.
IEEE DOI 1202
BibRef

Subburaman, V.B.[Venkatesh Bala], Descamps, A.[Adrien], Carincotte, C.[Cyril],
Counting People in the Crowd Using a Generic Head Detector,
AVSS12(470-475).
IEEE DOI 1211
BibRef

Zhang, Y., Yao, D., Qiu, T.Z., Peng, L., Zhang, Y.,
Pedestrian Safety Analysis in Mixed Traffic Conditions Using Video Data,
ITS(13), No. 4, December 2012, pp. 1832-1844.
IEEE DOI 1212
BibRef

Budge, S.E., Sallay, J.A., Wang, Z., Gunther, J.H.,
People Matching for Transportation Planning Using Texel Camera Data for Sequential Estimation,
SMCS(43), No. 3, May 2013, pp. 619-629.
IEEE DOI 1305
BibRef

Conte, D.[Donatello], Foggia, P.[Pasquale], Percannella, G.[Gennaro], Vento, M.[Mario],
Counting moving persons in crowded scenes,
MVA(24), No. 5, July 2013, pp. 1029-1042.
Springer DOI 1306
BibRef
Earlier:
A Method Based on the Indirect Approach for Counting People in Crowded Scenes,
AVSS10(111-118).
IEEE DOI 1009
See also Graph-Kernel Method for Re-identification, A. BibRef

Conte, D.[Dajana], Foggia, P.[Pasquale], Percannella, G.[Gennaro], Tufano, F.[Francesco], Vento, M.[Mario],
Reflection Removal for People Detection in Video Surveillance Applications,
CIAP11(I: 178-186).
Springer DOI 1109
BibRef
Earlier:
Reflection Removal in Color Videos,
ICPR10(1788-1791).
IEEE DOI 1008
BibRef

Conte, D.[Donatello], Foggia, P.[Pasquale], Percannella, G.[Gennaro], Tufano, F.[Francesco], Vento, M.[Mario],
A Method for Counting People in Crowded Scenes,
AVSS10(225-232).
IEEE DOI 1009
BibRef
And:
Counting Moving People in Videos by Salient Points Detection,
ICPR10(1743-1746).
IEEE DOI 1008
BibRef
Earlier:
An Algorithm for Detection of Partially Camouflaged People,
AVSBS09(340-345).
IEEE DOI 0909
See also Reflection Removal in Color Videos. BibRef

Percannella, G.[Gennaro], Vento, M.[Mario],
A Self-trainable System for Moving People Counting by Scene Partitioning,
ICIAR11(II: 297-306).
Springer DOI 1106
BibRef

Cherian, A.[Anoop], Sra, S.[Suvrit], Banerjee, A.[Arindam], Papanikolopoulos, N.P.[Nikolaos P.],
Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices,
PAMI(35), No. 9, 2013, pp. 2161-2174.
IEEE DOI 1307
BibRef
Earlier:
Efficient similarity search for covariance matrices via the Jensen-Bregman LogDet Divergence,
ICCV11(2399-2406).
IEEE DOI 1201
Covariance matrix as feature descriptors for people tracking, etc. See also Efficient Nearest Neighbors via Robust Sparse Hashing. BibRef

Cherian, A.[Anoop], Sra, S.[Suvrit],
Riemannian Sparse Coding for Positive Definite Matrices,
ECCV14(III: 299-314).
Springer DOI 1408
BibRef

Cherian, A.[Anoop], Morellas, V.[Vassilios], Papanikolopoulos, N.P.[Nikolaos P.], Bedros, S.J.[Saad J.],
Dirichlet process mixture models on symmetric positive definite matrices for appearance clustering in video surveillance applications,
CVPR11(3417-3424).
IEEE DOI 1106
BibRef

Sivalingam, R.[Ravishankar], Boley, D.L.[Daniel L.], Morellas, V.[Vassilios], Papanikolopoulos, N.P.[Nikolaos P.],
Tensor Sparse Coding for Positive Definite Matrices,
PAMI(36), No. 3, March 2014, pp. 592-605.
IEEE DOI 1403
BibRef
Earlier:
Positive definite dictionary learning for region covariances,
ICCV11(1013-1019).
IEEE DOI 1201
BibRef
Earlier:
Tensor Sparse Coding for Region Covariances,
ECCV10(IV: 722-735).
Springer DOI 1009
computer vision BibRef

Sivalingam, R., Boley, D., Morellas, V., Papanikolopoulos, N.,
Tensor Dictionary Learning for Positive Definite Matrices,
IP(24), No. 11, November 2015, pp. 4592-4601.
IEEE DOI 1509
Covariance matrices BibRef

Fehr, D.[Duc], Sivalingam, R.[Ravishankar], Morellas, V.[Vassilios], Papanikolopoulos, N.P.[Nikolaos P.], Lotfallah, O.[Osama], Park, Y.C.[Young-Choon],
Counting People in Groups,
AVSBS09(152-157).
IEEE DOI 0909
BibRef

Maddalena, L.[Lucia], Petrosino, A.[Alfredo], Russo, F.[Francesco],
People counting by learning their appearance in a multi-view camera environment,
PRL(36), No. 1, 2014, pp. 125-134.
Elsevier DOI 1312
Artificial neural network BibRef

Kataoka, H.[Hirokatsu], Tamura, K.[Kimimasa], Iwata, K.[Kenji], Satoh, Y.[Yutaka], Matsui, Y.[Yasuhiro], Aoki, Y.[Yoshimitsu],
Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety,
IEICE(E97-D), No. 2, February 2013, pp. 296-304.
WWW Link. 1402
BibRef

Kataoka, H.[Hirokatsu], Hashimoto, K.[Kiyoshi], Iwata, K.[Kenji], Satoh, Y.[Yutaka], Navab, N.[Nassir], Ilic, S.[Slobodan], Aoki, Y.[Yoshimitsu],
Extended Co-occurrence HOG with Dense Trajectories for Fine-Grained Activity Recognition,
ACCV14(V: 336-349).
Springer DOI 1504
BibRef

Reyes, F., Cipriano, A.,
On-line passenger estimation in a metro system using particle filter,
IET-ITS(8), No. 1, February 2014, pp. 1-8.
DOI Link 1406
digital simulation BibRef

Liu, S., Lo, S., Ma, J., Wang, W.,
An Agent-Based Microscopic Pedestrian Flow Simulation Model for Pedestrian Traffic Problems,
ITS(15), No. 3, June 2014, pp. 992-1001.
IEEE DOI 1407
Adaptation models BibRef

Zhang, Y., Yao, D., Qiu, T.Z., Peng, L.,
Scene-based pedestrian safety performance model in mixed traffic situation,
IET-ITS(8), No. 3, May 2014, pp. 209-218.
DOI Link 1407
BibRef

Wang, J.Q.[Jin-Qiao], Fu, W.[Wei], Liu, J.J.[Jing-Jing], Lu, H.Q.[Han-Qing],
Spatiotemporal Group Context for Pedestrian Counting,
CirSysVideo(24), No. 9, September 2014, pp. 1620-1630.
IEEE DOI 1410
Markov processes BibRef

Puyol, M.G., Bobkov, D., Robertson, P., Jost, T.,
Pedestrian Simultaneous Localization and Mapping in Multistory Buildings Using Inertial Sensors,
ITS(15), No. 4, August 2014, pp. 1714-1727.
IEEE DOI 1410
autoregressive moving average processes BibRef

Ryan, D.[David], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
An evaluation of crowd counting methods, features and regression models,
CVIU(130), No. 1, 2015, pp. 1-17.
Elsevier DOI 1411
BibRef
Earlier:
Scene Invariant Crowd Counting,
DICTA11(237-242).
IEEE DOI 1205
BibRef
Earlier: A1, A2, A4, A3:
Crowd Counting Using Group Tracking and Local Features,
AVSS10(218-224).
IEEE DOI 1009
BibRef
Earlier: A1, A2, A4, A3:
Crowd Counting Using Multiple Local Features,
DICTA09(81-88).
IEEE DOI 0912
See also Textures of optical flow for real-time anomaly detection in crowds. Crowd counting BibRef

Xu, J.X.[Jing-Xin], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Activity Analysis in Complicated Scenes Using DFT Coefficients of Particle Trajectories,
AVSS12(82-87).
IEEE DOI 1211
BibRef
Earlier:
Activity Modelling in Crowded Environments: A Soft-Decision Approach,
DICTA11(107-112).
IEEE DOI 1205
BibRef

Barabino, B., Di Francesco, M., Mozzoni, S.,
An Offline Framework for Handling Automatic Passenger Counting Raw Data,
ITS(15), No. 6, December 2014, pp. 2443-2456.
IEEE DOI 1412
data handling BibRef

Barabino, B., Di Francesco, M., Mozzoni, S.,
An Offline Framework for the Diagnosis of Time Reliability by Automatic Vehicle Location Data,
ITS(18), No. 3, March 2017, pp. 583-594.
IEEE DOI 1703
Biological system modeling BibRef

Islam, M.K., Vandebona, U., Dixit, V.V., Sharma, A.,
A Bulk Queue Model for the Evaluation of Impact of Headway Variations and Passenger Waiting Behavior on Public Transit Performance,
ITS(15), No. 6, December 2014, pp. 2432-2442.
IEEE DOI 1412
Markov processes BibRef

Islam, M.K., Vandebona, U., Dixit, V.V., Sharma, A.,
A Model to Evaluate the Impact of Headway Variation and Vehicle Size on the Reliability of Public Transit,
ITS(16), No. 4, August 2015, pp. 1840-1850.
IEEE DOI 1508
Analytical models BibRef

Chen, W.G.[Wei-Gang], Wang, X.[Xun], Wang, H.Y.[Hui-Yan], Peng, H.Y.[Hao-Yu],
Hybrid approach using map-based estimation and class-specific Hough forest for pedestrian counting and detection,
IET-IPR(8), No. 12, 2014, pp. 771-781.
DOI Link 1412
Hough transforms BibRef

Tang, N.C., Lin, Y.Y.[Yen-Yu], Weng, M.F.[Ming-Fang], Liao, H.Y.M.,
Cross-Camera Knowledge Transfer for Multiview People Counting,
IP(24), No. 1, January 2015, pp. 80-93.
IEEE DOI 1502
feature extraction BibRef

Zhang, S.S.[Shan-Shan], Bauckhage, C.[Christian], Cremers, A.B.[Armin B.],
Efficient Pedestrian Detection via Rectangular Features Based on a Statistical Shape Model,
ITS(16), No. 2, April 2015, pp. 763-775.
IEEE DOI 1504
Computational modeling BibRef
Earlier:
Informed Haar-Like Features Improve Pedestrian Detection,
CVPR14(947-954)
IEEE DOI 1409
BibRef

Zhang, S.S.[Shan-Shan], Bauckhage, C.[Christian], Klein, D.A.[Dominik A.], Cremers, A.B.[Armin B.],
Exploring Human Vision Driven Features for Pedestrian Detection,
CirSysVideo(25), No. 10, October 2015, pp. 1709-1720.
IEEE DOI 1511
BibRef
Earlier: A1, A3, A2, A4:
Center-Surround Contrast Features for Pedestrian Detection,
ICPR14(2293-2298)
IEEE DOI 1412
Detectors BibRef
Earlier: A1, A2, A3, A4:
Moving pedestrian detection based on motion segmentation,
WORV13(102-107)
IEEE DOI 1307
collision avoidance BibRef

Iryo-Asano, M., Alhajyaseen, W.K.M., Nakamura, H.,
Analysis and Modeling of Pedestrian Crossing Behavior During the Pedestrian Flashing Green Interval,
ITS(16), No. 2, April 2015, pp. 958-969.
IEEE DOI 1504
Analytical models BibRef

Beecroft, M., Pangbourne, K.,
Personal security in travel by public transport: The role of traveller information and associated technologies,
IET-ITS(9), No. 2, 2015, pp. 167-174.
DOI Link 1504
public transport BibRef

Foroughi, H.[Homa], Ray, N.[Nilanjan], Zhang, H.[Hong],
Robust people counting using sparse representation and random projection,
PR(48), No. 10, 2015, pp. 3038-3052.
Elsevier DOI 1507
People counting BibRef

Li, H., Chan, E.C.L., Guo, X., Xiao, J., Wu, K., Ni, L.M.,
Wi-Counter: Smartphone-Based People Counter Using Crowdsourced Wi-Fi Signal Data,
HMS(45), No. 4, August 2015, pp. 442-452.
IEEE DOI 1506
IEEE 802.11 Standards. Not vision based. BibRef

Xia, W., Zhang, J., Kruger, U.,
Semisupervised Pedestrian Counting With Temporal and Spatial Consistencies,
ITS(16), No. 4, August 2015, pp. 1705-1715.
IEEE DOI 1508
Bismuth BibRef

Mukherjee, S.[Satarupa], Gil, S.[Stephani], Ray, N.[Nilanjan],
Unique people count from monocular videos,
VC(31), No. 10, October 2015, pp. 1405-1417.
WWW Link. 1509
BibRef

Zhang, X.G.[Xu-Guang], He, H.M.[Hai-Ming], Cao, S.K.[Shu-Kai], Liu, H.H.[Hong-Hai],
Flow field texture representation-based motion segmentation for crowd counting,
MVA(26), No. 7-8, November 2015, pp. 871-883.
WWW Link. 1511
BibRef

Vera, P.[Pablo], Monjaraz, S.[Sergio], Salas, J.[Joaquín],
Counting pedestrians with a zenithal arrangement of depth cameras,
MVA(27), No. 2, February 2016, pp. 303-315.
WWW Link. 1602
BibRef

Hu, Y.C.[Yao-Cong], Chang, H.[Huan], Nian, F.D.[Fu-Dong], Wang, Y.[Yan], Li, T.[Teng],
Dense Crowd Counting from Still Images with Convolutional Neural Networks,
JVCIR(38), No. 1, 2016, pp. 530-539.
Elsevier DOI 1605
Crowd counting BibRef

Chen, K., Kämäräinen, J.K.,
Pedestrian Density Analysis in Public Scenes With Spatiotemporal Tensor Features,
ITS(17), No. 7, July 2016, pp. 1968-1977.
IEEE DOI 1608
feature extraction BibRef

Al-Zaydi, Z.Q.H.[Zeyad Q.H.], Ndzi, D.L.[David L.], Yang, Y.[Yanyan], Kamarudin, M.L.[Munirah L.],
An adaptive people counting system with dynamic features selection and occlusion handling,
JVCIR(39), No. 1, 2016, pp. 218-225.
Elsevier DOI 1608
Crowd counting BibRef

Del Pizzo, L.[Luca], Foggia, P.[Pasquale], Greco, A.[Antonio], Percannella, G.[Gennaro], Vento, M.[Mario],
Counting people by RGB or depth overhead cameras,
PRL(81), No. 1, 2016, pp. 41-50.
Elsevier DOI 1609
People counting BibRef

Zhang, N.[Ningyu], Chen, H.J.[Hua-Jun], Chen, X.[Xi], Chen, J.[Jiaoyan],
Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies,
IJGI(5), No. 10, 2016, pp. 180.
DOI Link 1610
BibRef

Guo, Y.[Yanyong], Sayed, T.[Tarek], Zaki, M.H.[Mohamed H.],
Automated analysis of pedestrian walking behaviour at a signalised intersection in China,
IET-ITS(11), No. 1, February 2017, pp. 28-36.
DOI Link 1703
BibRef

Chen, K., Zhang, Z.,
Pedestrian Counting With Back-Propagated Information and Target Drift Remedy,
SMCS(47), No. 4, April 2017, pp. 639-647.
IEEE DOI 1704
Cybernetics BibRef

Rosado, A.L.[A. López], Chien, S., Li, L., Yi, Q., Chen, Y., Sherony, R.,
Certainty and Critical Speed for Decision Making in Tests of Pedestrian Automatic Emergency Braking Systems,
ITS(18), No. 6, June 2017, pp. 1358-1370.
IEEE DOI 1706
Analytical models, Automobiles, Computer crashes, Decision making, Safety, Vehicle crash testing, Pedestrian protection, active safety margin, critical speed for decision making, prediction, model BibRef

Niu, Q.[Qun], Wu, H.F.[He-Feng], Gao, C.Y.[Cheng-Ying], Luo, X.N.[Xiao-Nan],
Laser-Based Bidirectional Pedestrian Counting via Height Map Guided Regression and Voting,
SIViP(11), No. 5, July 2017, pp. 897-904.
WWW Link. 1706
BibRef


Soares, G.S.[Guilherme S.], Machado, R.C.[Rubens C.], Lotufo, R.A.[Roberto A.],
People-Flow Counting Using Depth Images for Embedded Processing,
ICIAR17(239-246).
Springer DOI 1706
BibRef

Wang, T.[Tao], Li, G.[Guohui], Lei, J.[Jun], Li, S.[Shuohao], Xu, S.[Shukui],
Crowd Counting Based on MMCNN in Still Images,
SCIA17(I: 468-479).
Springer DOI 1706
BibRef

Elassal, N.[Nada], Elder, J.H.[James H.],
Unsupervised Crowd Counting,
ACCV16(V: 329-345).
Springer DOI 1704
BibRef

Saqib, M., Daud Khan, S., Blumenstein, M.,
Texture-based feature mining for crowd density estimation: A study,
ICVNZ16(1-6)
IEEE DOI 1701
Cameras BibRef

Siva, P., Shafiee, M.J., Jamieson, M., Wong, A.,
Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG),
ECVW16(885-892)
IEEE DOI 1612
BibRef

Zhang, Y., Zhou, D., Chen, S., Gao, S., Ma, Y.,
Single-Image Crowd Counting via Multi-Column Convolutional Neural Network,
CVPR16(589-597)
IEEE DOI 1612
BibRef

von Borstel, M.[Matthias], Kandemir, M.[Melih], Schmidt, P.[Philip], Rao, M.K.[Madhavi K.], Rajamani, K.[Kumar], Hamprecht, F.A.[Fred A.],
Gaussian Process Density Counting from Weak Supervision,
ECCV16(I: 365-380).
Springer DOI 1611
cells and pedestrians BibRef

Sourtzinos, P.[Panos], Velastin, S.A.[Sergio A.], Jara, M.[Miguel], Zegers, P.[Pablo], Makris, D.[Dimitrios],
People Counting in Videos by Fusing Temporal Cues from Spatial Context-Aware Convolutional Neural Networks,
Crowd16(II: 655-667).
Springer DOI 1611
BibRef

Shimizu, M., Oizumi, J., Matsuoka, R., Takeda, H., Okukura, H., Ooya, A., Koike, A.,
Development Of A Novel System To Measure A Clearance Of A Passenger Platform,
ISPRS16(B5: 573-580).
DOI Link 1610
BibRef

Wang, Y., Zou, Y.,
Fast visual object counting via example-based density estimation,
ICIP16(3653-3657)
IEEE DOI 1610
Estimation BibRef

Shang, C., Ai, H., Bai, B.,
End-to-end crowd counting via joint learning local and global count,
ICIP16(1215-1219)
IEEE DOI 1610
Computational modeling BibRef

Zalluhoglu, C.[Cemil], Ikizler-Cinbis, N.[Nazli],
Counting People in Crowded Scenes via Detection and Regression Fusion,
ICIAR16(309-317).
Springer DOI 1608
BibRef

Kocamaz, M.K., Gong, J., Pires, B.R.,
Vision-based counting of pedestrians and cyclists,
WACV16(1-8)
IEEE DOI 1606
Cameras BibRef

Xu, B., Qiu, G.,
Crowd density estimation based on rich features and random projection forest,
WACV16(1-8)
IEEE DOI 1606
Computational modeling BibRef

Kaminski, L., Gardzinski, P., Kowalak, K., Mackowiak, S.,
Unsupervised abnormal crowd activity detection in surveillance systems,
WSSIP16(1-4)
IEEE DOI 1608
BibRef
Earlier: A2, A3, A1, A4:
Crowd density estimation based on voxel model in multi-view surveillance systems,
WSSIP15(216-219)
IEEE DOI 1603
image classification BibRef

Pham, V.Q., Kozakaya, T., Yamaguchi, O., Okada, R.,
COUNT Forest: CO-Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation,
ICCV15(3253-3261)
IEEE DOI 1602
Computational modeling BibRef

Khan, U.[Usman], Klette, R.[Reinhard],
Logarithmically Improved Property Regression for Crowd Counting,
PSIVT15(123-135).
Springer DOI 1602
BibRef

Yang, R.[Ren], Xu, H.Z.[Hua-Zhong], Wang, J.Q.[Jin-Qiao],
Robust Crowd Segmentation and Counting in Indoor Scenes,
MMMod16(I: 505-514).
Springer DOI 1601
BibRef

Hung, D.H.[Dao Huu], Saito, H., Yamamoto, K., Sato, H.,
An omnidirectional vision system for bus safety surveillance,
AVSS15(1-6)
IEEE DOI 1511
cameras BibRef

Cunha, P.[Pedro], Moura, D.C.[Daniel C.],
A scalable and privacy preserving approach for counting pedestrians in urban environment,
AVSS15(1-6)
IEEE DOI 1511
Cameras BibRef

Segui, S.[Santi], Pujol, O.[Oriol], Vitria, J.[Jordi],
Learning to count with deep object features,
DeepLearn15(90-96)
IEEE DOI 1510
Accuracy. Counting, not detect and locate individual instances. BibRef

Chen, S.[Sheng], Fern, A.[Alan], Todorovic, S.[Sinisa],
Person count localization in videos from noisy foreground and detections,
CVPR15(1364-1372)
IEEE DOI 1510
BibRef

Zhao, Z.[Zhuoyi], Li, H.[Hongsheng], Zhao, R.[Rui], Wang, X.G.[Xiao-Gang],
Crossing-Line Crowd Counting with Two-Phase Deep Neural Networks,
ECCV16(VIII: 712-726).
Springer DOI 1611
BibRef

Zhang, C.[Cong], Li, H.[Hongsheng], Wang, X.G.[Xiao-Gang], Yang, X.K.[Xiao-Kang],
Cross-scene crowd counting via deep convolutional neural networks,
CVPR15(833-841)
IEEE DOI 1510
BibRef

Xu, J.S.[Jing-Song], Wu, Q.A.[Qi-Ang], Zhang, J.[Jian], Silk, B., Ngo, G.T.[Gia Thuan], Tang, Z.M.[Zhen-Min],
Efficient People Counting with Limited Manual Interferences,
DICTA14(1-6)
IEEE DOI 1502
feature extraction BibRef

Hegner, R.[Robert], Hartmann, A.[Andreas], Niederberger, T.[Thomas], Schuster, G.M.[Guido M],
Scalable, self-organizing 3D camera network for non-intrusive people tracking and counting,
ICIP14(3405-3407)
IEEE DOI 1502
Calibration BibRef

Yu, Z.J.[Zhong-Jie], Gong, C.[Chen], Yang, J.[Jie], Bai, L.[Li],
Pedestrian counting based on spatial and temporal analysis,
ICIP14(2432-2436)
IEEE DOI 1502
Bandwidth BibRef

Akai, R.[Ryota], Nitta, N.[Naoko], Babaguchi, N.[Noboru],
Real-Time People Counting across Spatially Adjacent Non-overlapping Camera Views,
MMMod15(I: 71-82).
Springer DOI 1501
BibRef

Luo, J.[Jun], Wang, J.Q.[Jin-Qiao], Xu, H.Z.[Hua-Zhong], Lu, H.Q.[Han-Qing],
A Real-Time People Counting Approach in Indoor Environment,
MMMod15(I: 214-223).
Springer DOI 1501
BibRef

Kumagai, S.[Shohei], Hotta, K.[Kazuhiro],
HLAC between Cells of HOG Feature for Crowd Counting,
ISVC14(I: 688-697).
Springer DOI 1501
BibRef

Pedersen, J.B., Markussen, J.B., Philipsen, M.P., Jensen, M.B., Moeslund, T.B.,
Counting the Crowd at a Carnival,
ISVC14(II: 706-715).
Springer DOI 1501
BibRef

Tabuchi, Y.[Yoshimune], Takahashi, T.[Tomokazu], Deguchi, D.[Daisuke], Ide, I.[Ichiro], Murase, H.[Hiroshi], Kurozumi, T.[Takayuki], Kashino, K.[Kunio],
Spatial People Density Estimation from Multiple Viewpoints by Memory Based Regression,
ICPR14(2209-2214)
IEEE DOI 1412
Cameras BibRef

Mora-Colque, R.V.H.[Rensso V. H.], Cámara-Chávez, G.[Guillermo], Schwartz, W.R.[William Robson],
Detection of Groups of People in Surveillance Videos Based on Spatio-Temporal Clues,
CIARP14(948-955).
Springer DOI 1411
BibRef

Topkaya, I.S.[Ibrahim Saygin], Erdogan, H.[Hakan], Porikli, F.M.[Fatih M.],
Counting people by clustering person detector outputs,
AVSS14(313-318)
IEEE DOI 1411
Clustering algorithms BibRef

Bondi, E.[Enrico], Seidenari, L.[Lorenzo], Bagdanov, A.D.[Andrew D.], Del Bimbo, A.[Alberto],
Real-time people counting from depth imagery of crowded environments,
AVSS14(337-342)
IEEE DOI 1411
Cameras BibRef

Ozer, B.[Burak], Wolf, M.[Marilyn],
A Train Station Surveillance System: Challenges and Solutions,
ECVW14(652-657)
IEEE DOI 1409
gesture recognitionin; surveillance; tracking BibRef

Chua, T.W.[Teck Wee], Leman, K.[Karianto], Gao, F.[Feng],
Hierarchical Audio-Visual Surveillance for Passenger Elevators,
MMMod14(II: 44-55).
Springer DOI 1405
BibRef

Hu, Y.[Yang], Liao, S.C.[Sheng-Cai], Yi, D.[Dong], Lei, Z.[Zhen], Li, S.Z.[Stan Z.],
Multi-camera Trajectory Mining: Database and Evaluation,
ICPR14(4684-4689)
IEEE DOI 1412
Cameras BibRef

Zhu, J.Q.[Jian-Qing], Liao, S.C.[Sheng-Cai], Lei, Z.[Zhen], Li, S.Z.[Stan Z.],
Improve Pedestrian Attribute Classification by Weighted Interactions from Other Attributes,
HIS14(545-557).
Springer DOI 1504
BibRef

Zhu, J.Q.[Jian-Qing], Liao, S.C.[Sheng-Cai], Lei, Z.[Zhen], Yi, D.[Dong], Li, S.Z.,
Pedestrian Attribute Classification in Surveillance: Database and Evaluation,
LSVSM13(331-338)
IEEE DOI 1403
feature extraction BibRef

Loy, C.C.[Chen Change], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
From Semi-supervised to Transfer Counting of Crowds,
ICCV13(2256-2263)
IEEE DOI 1403
crowd counting BibRef

Noceti, N.[Nicoletta], Odone, F.[Francesca],
Semi-supervised learning of sparse representations to recognize people spatial orientation,
ICIP14(3382-3386)
IEEE DOI 1502
Accuracy BibRef

Zini, L.[Luca], Noceti, N.[Nicoletta], Odone, F.[Francesca],
Precise people counting in real time,
ICIP13(3592-3596)
IEEE DOI 1402
people counting BibRef

Jeong, C.Y.[Chi Yoon], Choi, S.[SuGil], Han, S.W.[Seung Wan],
A method for counting moving and stationary people by interest point classification,
ICIP13(4545-4548)
IEEE DOI 1402
People counting BibRef

Fradi, H.[Hajer], Dugelay, J.L.[Jean-Luc],
A new multiclass SVM algorithm and its application to crowd density analysis using LBP features,
ICIP13(4554-4558)
IEEE DOI 1402
Crowd density BibRef

Nitta, N.[Naoko], Nakazaki, T.[Takayuki], Nakamura, K.[Kazuaki], Akai, R.[Ryota], Babaguchi, N.[Noboru],
People counting across spatially disjoint cameras by flow estimation between foreground regions,
AVSS13(414-419)
IEEE DOI 1311
Cameras BibRef

Galcík, F.[František], Gargalík, R.[Radoslav],
Real-Time Depth Map Based People Counting,
ACIVS13(330-341).
Springer DOI 1311
BibRef

Casola, V.[Valentina], Esposito, M.[Mariana], Flammini, F.[Francesco], Mazzocca, N.[Nicola],
Performance Evaluation of Video Analytics for Surveillance On-Board Trains,
ACIVS13(414-425).
Springer DOI 1311
BibRef

Zhu, L.[Lei], Wong, K.H.[Kin-Hong],
Human Tracking and Counting Using the KINECT Range Sensor Based on Adaboost and Kalman Filter,
ISVC13(II:582-591).
Springer DOI 1311
BibRef

Roncancio, H.[Henry], Hernandes, A.C.[Andre Carmona], Becker, M.[Marcelo],
Ceiling analysis of pedestrian recognition pipeline for an autonomous car application,
WORV13(215-220)
IEEE DOI 1307
BibRef

Neumann, J.[Joachim], Zao, M.Q.[Man-Qi], Karatzoglou, A.[Alexandros], Oliver, N.[Nuria],
Event Detection in Communication and Transportation Data,
IbPRIA13(827-838).
Springer DOI 1307
BibRef

Scoleri, T., Henneberg, M.,
View-Independent Prediction of Body Dimensions in Crowded Environments,
DICTA12(1-8).
IEEE DOI 1303
BibRef

Nguyen, N.H.[Ngoc Hung], Hartley, R.I.,
Height Measurement for Humans in Motion Using a Camera: A Comparison of Different Methods,
DICTA12(1-8).
IEEE DOI 1303
BibRef

Lin, Y.[Yujie], Liu, N.[Ning],
Integrating bottom-up and top-down processes for accurate pedestrian counting,
ICPR12(2508-2511).
WWW Link. 1302
BibRef

Chen, K.[Ke], Loy, C.C.[Chen Change], Gong, S.G.[Shao-Gang], Xiang, T.[Tony],
Feature Mining for Localised Crowd Counting,
BMVC12(21).
DOI Link 1301
BibRef

Li, J.W.[Jing-Wen], Huang, L.[Lei], Liu, C.P.[Chang-Ping],
People Counting across Multiple Cameras for Intelligent Video Surveillance,
AVSS12(178-183).
IEEE DOI 1211
BibRef

Zhang, X.C.[Xu-Cong], Yan, J.J.[Jun-Jie], Feng, S.K.[Shi-Kun], Lei, Z.[Zhen], Yi, D.[Dong], Li, S.Z.[Stan Z.],
Water Filling: Unsupervised People Counting via Vertical Kinect Sensor,
AVSS12(215-220).
IEEE DOI 1211
BibRef

Kim, D.[Daehum], Lee, Y.H.[Young-Hyun], Ku, B.H.[Bon-Hwa], Ko, H.S.[Han-Seok],
Crowd Density Estimation Using Multi-class Adaboost,
AVSS12(447-451).
IEEE DOI 1211
BibRef

Zhang, Z.[Zhong], Yin, W.H.[Wei-Hong], Venetianer, P.L.[Peter L.],
Fast Crowd Density Estimation in Surveillance Videos without Training,
AVSS12(452-457).
IEEE DOI 1211
BibRef

Ogawa, M.[Masahiro], Fukamachi, H.[Hideo], Funayama, R.[Ryuji], Kindo, T.[Toshiki],
CYKLS: Detect Pedestrian's Dart Focusing on an Appearance Change,
CVVT12(II: 556-565).
Springer DOI 1210
Driver assistance BibRef

Hsieh, J.W.[Jun-Wei], Fang, F.J.[Fu-Jiang], Lin, G.J.[Guo-Jin], Wang, Y.S.[Yu-Shi],
Template Matching and Monte Carlo Markova Chain for People Counting under Occlusions,
MMMod12(761-771).
Springer DOI 1201
BibRef

Mukherjee, S.[Satarupa], Saha, B.N.[Baidya-Nath], Jamal, I.[Iqbal], Leclerc, R.[Richard], Ray, N.[Nilanjan],
Anovel framework for automatic passenger counting,
ICIP11(2969-2972).
IEEE DOI 1201
BibRef

Xing, J.L.[Jun-Liang], Ai, H.Z.[Hai-Zhou], Liu, L.W.[Li-Wei], Lao, S.H.[Shi-Hong],
Robust crowd counting using detection flow,
ICIP11(2061-2064).
IEEE DOI 1201
BibRef

Favoreel, W.[Wouter],
Pedestrian sensing for increased traffic safety and efficiency at signalized intersections,
AVSBS11(539-542).
IEEE DOI 1111
AVSS 2011 demo session. BibRef

Li, J.W.[Jing-Wen], Huang, L.[Lei], Liu, C.P.[Chang-Ping],
Online adaptive learning for multi-camera people counting,
ICPR12(3415-3418).
WWW Link. 1302
BibRef
Earlier:
Robust people counting in video surveillance: Dataset and system,
AVSBS11(54-59).
IEEE DOI 1111
BibRef

Rosner, M.[Marcin],
Intelligent crossing sensor and vehicle detector,
AVSBS11(535).
IEEE DOI 1111
AVSS 2011 demo session: BibRef

Leoputra, W.S., Venkatesh, S., Tan, T.[Tele],
Pedestrian detection for mobile bus surveillance,
ICARCV08(726-732).
IEEE DOI 1109
BibRef
And:
Passenger monitoring in moving bus video,
ICARCV08(719-725).
IEEE DOI 1109
BibRef

Lovell, B.C., Chen, S., Bigdeli, A., Berglund, E., Sanderson, C.,
On intelligent surveillance systems and face recognition for mass transport security,
ICARCV08(713-718).
IEEE DOI 1109
BibRef

Déniz-Suárez, O.[Oscar], Castrillón-Santana, M.[Modesto], Lorenzo-Navarro, J.[Javier], Bueno, G.[Gloria], Hernández, M.[Mario],
Fast Classification in Incrementally Growing Spaces,
IbPRIA11(305-312).
Springer DOI 1106
BibRef

Hernández-Sosa, D.[Daniel], Castrillón-Santana, M.[Modesto], Lorenzo-Navarro, J.[Javier],
Multi-sensor People Counting,
IbPRIA11(321-328).
Springer DOI 1106
BibRef

Elmarhomy, A.[Ahmed], Karungaru, S.[Stephen], Terada, K.[Kenji],
A method for counting passersby using time-space image,
FCV11(1-5).
IEEE DOI 1102
BibRef

Su, H.[Hang], Yang, H.[Hua], Zheng, S.[Shibao],
The Large-Scale Crowd Density Estimation Based on Effective Region Feature Extraction Method,
ACCV10(III: 302-313).
Springer DOI 1011
BibRef

Patzold, M., Sikora, T.,
Real-time person counting by propagating networks flows,
AVSBS11(66-70).
IEEE DOI 1111
BibRef

Patzold, M., Evangelio, R.H.[Ruben Heras], Sikora, T.[Thomas],
Counting People in Crowded Environments by Fusion of Shape and Motion Information,
AVSS10(157-164).
IEEE DOI 1009
BibRef

Benabbas, Y.[Yassine], Ihaddadene, N.[Nacim], Yahiaoui, T., Urruty, T., Djeraba, C.[Chabane],
Spatio-Temporal Optical Flow Analysis for People Counting,
AVSS10(212-217).
IEEE DOI 1009
BibRef

Merad, D.[Djamel], Aziz, K.E.[Kheir Eddine], Thome, N.[Nicolas],
Fast People Counting Using Head Detection From Skeleton Graph,
AVSS10(151-156).
IEEE DOI 1009
BibRef
And: AVSS10(233-240).
IEEE DOI 1009
See also Person Re-identification Using Appearance Classification. BibRef

Gasparini, L., Manduchi, R., Gottardi, M.,
An Ultra-Low-Power Contrast-Based Integrated Camera Node and its Application as a People Counter,
AVSS10(547-554).
IEEE DOI 1009
BibRef

Miller, P., Liu, W.[Weiru], Fowler, C., Zhou, H.Y.[Hui-Yu], Shen, J.[Jiali], Ma, J.B.[Jian-Bing], Zhang, J.G.[Jian-Guo], Yan, W.[Wei_Qi], McLaughlin, K., Sezer, S.,
Intelligent Sensor Information System For Public Transport: To Safely Go ...,
AVSS10(533-538).
IEEE DOI 1009
BibRef

Szczot, M.[Magdalena], Dannenmann, I.[Iris], Lohlein, O.[Otto],
Incorporating Lane Estimation as Context Source in Pedestrian Recognition Task,
ICPR10(2628-2631).
IEEE DOI 1008
BibRef

Pham, Q.C.[Quoc-Cuong], Lapeyronnie, A.[Agnes], Baudry, C.[Christelle], Lucat, L.[Laurent], Sayd, P.[Patrick], Ambellouis, S.[Sebastien], Sodoyer, D.[David], Flancquart, A.[Amaury], Barcelo, A.C.[Alain-Claude], Heer, F.[Frederic], Ganansia, F.[Fabrice], Delcourt, V.[Vincent],
Audio-video surveillance system for public transportation,
IPTA10(47-53).
IEEE DOI 1007
BibRef

Kembhavi, A.[Aniruddha], Yeh, T.[Tom], Davis, L.S.[Larry S.],
Why Did the Person Cross the Road (There)? Scene Understanding Using Probabilistic Logic Models and Common Sense Reasoning,
ECCV10(II: 693-706).
Springer DOI 1009
BibRef

Schraml, S.[Stephan], Belbachir, A.N.[Ahmed Nabil],
A spatio-temporal clustering method using real-time motion analysis on event-based 3D vision,
VAM10(57-63).
IEEE DOI 1006
BibRef

Schraml, S.[Stephan], Belbachir, A.N.[Ahmed Nabil], Brandle, N.,
A real-time pedestrian classification method for event-based dynamic stereo vision,
ECVW10(93-99).
IEEE DOI 1006
BibRef

Belbachir, A.N., Schraml, S., Brandle, N.,
Real-time classification of pedestrians and cyclists for intelligent counting of non-motorized traffic,
SISM10(45-50).
IEEE DOI 1006
BibRef

Cao, Y.Z.[Yu-Zhen], Chen, L.S.[Lu-Shi], Jia, S.[Shuo],
An Image Based Detection of Pedestrian Crossing,
CISP09(1-5).
IEEE DOI 0910
BibRef

Antic, B.[Borislav], Letic, D.[Dragan], Culibrk, D.[Dubravko], Crnojevic, V.[Vladimir],
K-means based segmentation for real-time zenithal people counting,
ICIP09(2565-2568).
IEEE DOI 0911
BibRef

Doulamis, N.D.,
Evacuation Planning through Cognitive Crowd Tracking,
WSSIP09(1-4).
IEEE DOI 0906
BibRef

Terabayashi, K.[Kenji], Hashimoto, Y.[Yuki], Umeda, K.[Kazunori],
Measurement of Pedestrian Groups Using Subtraction Stereo,
ISVC09(II: 538-549).
Springer DOI 0911
BibRef

Zu, K.[Keju], Liu, F.Q.[Fu-Qiang], Li, Z.P.[Zhi-Peng],
Counting Pedestrian in Crowded Subway Scene,
CISP09(1-4).
IEEE DOI 0910
BibRef

Luling, Mu, P.[Ping'an], Dai, S.G.[Shu-Guang],
Research of Object Tracking Algorithm Applied in Passenger Flow Statistics in Public Traffic,
CISP09(1-3).
IEEE DOI 0910
BibRef

Ma, J.B.[Jian-Bing], Liu, W.[Weiru], Miller, P.[Paul], Yan, W.Q.[Wei-Qi],
Event Composition with Imperfect Information for Bus Surveillance,
AVSBS09(382-387).
IEEE DOI 0909
BibRef

Zhao, X.[Xi], Delleandrea, E.[Emmanuel], Chen, L.M.[Li-Ming],
A People Counting System Based on Face Detection and Tracking in a Video,
AVSBS09(67-72).
IEEE DOI 0909
BibRef

Cong, Y.[Yang], Gong, H.F.[Hai-Feng], Zhu, S.C.[Song-Chun], Tang, Y.D.[Yan-Dong],
Flow mosaicking: Real-time pedestrian counting without scene-specific learning,
CVPR09(1093-1100).
IEEE DOI 0906
BibRef

Fascioli, A.[Alessandra], Fedriga, R.I.[Rean Isabella], Ghidoni, S.[Stefano],
Vision-based monitoring of pedestrian crossings,
CIAP07(566-574).
IEEE DOI 0709
BibRef

Bertozzi, M., Broggi, A., Fascioli, A., Tibaldi, A., Chapuis, R., Chausse, F.,
Pedestrian localization and tracking system with Kalman filtering,
IVS04(584-589).
WWW Link. 0411
BibRef

Naturel, X.[Xavier], Odobez, J.M.[Jean-Marc],
Detecting queues at vending machines: A statistical layered approach,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Carter, N.L.[Nicholas L.], Ferryman, J.M.[James M.],
The SAFEE On-Board Threat Detection System,
CVS08(xx-yy).
Springer DOI 0805
BibRef

Arai, H.[Hiroyuki], Miyagawa, I.[Isao], Koike, H.[Hideki], Haseyama, M.[Miki],
Estimating the number of people in a video sequence via geometrical model,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Li, M.[Min], Zhang, Z.X.[Zhao-Xiang], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Robust visual tracking based on simplified biologically inspired features,
ICIP09(4113-4116).
IEEE DOI 0911
BibRef

Li, M.[Min], Zhang, Z.X.[Zhao-Xiang], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Pyramidal Statistics of Oriented Filtering for robust pedestrian detection,
VS09(1153-1160).
IEEE DOI 0910
BibRef
And:
Rapid and robust human detection and tracking based on omega-shape features,
ICIP09(2545-2548).
IEEE DOI 0911
BibRef
Earlier:
Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection,
ICPR08(1-4).
IEEE DOI 0812
See also Robust automated ground plane rectification based on moving vehicles for traffic scene surveillance. BibRef

Yahiaoui, T.[Tarek], Meurie, C.[Cyril], Khoudour, L.[Louahdi], Cabestaing, F.[François],
A People Counting System Based on Dense and Close Stereovision,
ICISP08(59-66).
Springer DOI 0807
BibRef

Teixeira, T., Savvides, A.,
Lightweight People Counting and Localizing in Indoor Spaces Using Camera Sensor Nodes,
ICDSC07(36-43).
IEEE DOI 0709
BibRef

Lee, G.G.[Gwang-Gook], Kim, B.S.[Byeoung-Su], Kim, W.Y.[Whoi-Yul],
Automatic Estimation of Pedestrian Flow,
ICDSC07(291-296).
IEEE DOI 0709
BibRef

Katz, I.[Itai], Aghajan, H.[Hamid],
Multiple camera-based chamfer matching for pedestrian detection,
ICDSC08(1-5).
IEEE DOI 0809
BibRef

Dong, L.[Lan], Parameswaran, V.[Vasu], Ramesh, V.[Visvanathan], Zoghlami, I.[Imad],
Fast Crowd Segmentation Using Shape Indexing,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Kong, S.[Suyu], Bhuyan, M.K., Sanderson, C., Lovell, B.C.[Brian C.],
Tracking of persons for video surveillance of unattended environments,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kong, S.[Suyu], Sanderson, C., Lovell, B.C.[Brian C.],
Classifying and tracking multiple persons for proactive surveillance of mass transport systems,
AVSBS07(159-163).
IEEE DOI 0709
BibRef

Valle, J.D., Oliveira, L.E.S., Koerich, A.L., Britto, A.S.,
People Counting in Low Density Video Sequences,
PSIVT07(737-748).
Springer DOI 0712
BibRef

Chee, B.C.[Boon Chong], Lazarescu, M.[Mihai], Tan, T.L.[Te-Le],
Detection and Monitoring of Passengers on a Bus by Video Surveillance,
CIAP07(143-148).
IEEE DOI 0709
BibRef

Bozzoli, M.[Massimiliano], Cinque, L.[Luigi],
A Statistical Method for People Counting in Crowded Environments,
CIAP07(506-511).
IEEE DOI 0709
BibRef

Septian, H., Tao, J.[Ji], Tan, Y.P.[Yap-Peng],
People Counting by Video Segmentation and Tracking,
ICARCV06(1-4).
IEEE DOI 0612
BibRef

Park, H.H.[Hyun Hee], Lee, H.G.[Hyung Gu], Noh, S.I.[Seung-In], Kim, J.H.[Jai-Hie],
Development of a Block-Based Real-Time People Counting System,
SSPR06(366-374).
Springer DOI 0608
BibRef

Celik, H., Hanjalic, A., Hendriks, E.A.,
Towards a Robust Solution to People Counting,
ICIP06(2401-2404).
IEEE DOI 0610
BibRef

Park, S.H.[Sang-Ho], Trivedi, M.M.[Mohan M.],
Analysis and query of person-vehicle interactions in homography domain,
VSSN06(101-110).
WWW Link. 0701
See also Two-stage Multi-view Analysis Framework for Human Activity and Interactions, A. BibRef

Sidla, O., Lypetskyy, Y., Brandle, N.[Norbert], Seer, S.[Stefan],
Pedestrian Detection and Tracking for Counting Applications in Crowded Situations,
AVSBS06(70-70).
IEEE DOI 0611
BibRef

Ploetner, J.[Jeffrey], Trivedi, M.M.[Mohan M.],
A multimodal approach for dynamic event capture of vehicles and pedestrians,
VSSN06(203-210).
WWW Link. 0701
BibRef

Steinbach, S.[Stephan], Rabaud, V.[Vincent], Belongie, S.J.[Serge J.],
Soylent Grid: It's Made of People,
ICV07(1-7).
IEEE DOI 0710
BibRef

Rabaud, V.[Vincent], Belongie, S.J.[Serge J.],
Counting Crowded Moving Objects,
CVPR06(I: 705-711).
IEEE DOI 0606
BibRef

Gray, D.[Douglas], Tao, H.[Hai],
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features,
ECCV08(I: 262-275).
Springer DOI 0810
BibRef

Kong, D.[Dan], Gray, D.[Doug], Tao, H.[Hai],
A Viewpoint Invariant Approach for Crowd Counting,
ICPR06(III: 1187-1190).
IEEE DOI 0609
BibRef
Earlier:
Counting Pedestrians in Crowds Using Viewpoint Invariant Training,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Jung, H.G.[Ho Gi], Lee, Y.H.[Yun Hee], Yoon, P.J.[Pal Joo], Hwang, I.Y.[In Yong], Kim, J.H.[Jai-Hie],
Sensor Fusion Based Obstacle Detection/Classification for Active Pedestrian Protection System,
ISVC06(II: 294-305).
Springer DOI 0611
BibRef

Lim, J.S.[Jong Seok], Kim, W.H.[Wook Hyun],
Detection and Tracking Multiple Pedestrians from a Moving Camera,
ISVC05(527-534).
Springer DOI 0512
BibRef

Bovyrin, A., Rodyushkin, K.,
Human height prediction and roads estimation for advanced video surveillance systems,
AVSBS05(219-223).
IEEE DOI 0602
Pedestrian surveillance. BibRef

Cavallaro, A.[Andrea],
Event Detection in Underground Stations Using Multiple Heterogeneous Surveillance Cameras,
ISVC05(535-542).
Springer DOI 0512
BibRef

Liu, X., Tu, P.H., Rittscher, J., Perera, A., Krahnstoever, N.O.,
Detecting and counting people in surveillance applications,
AVSBS05(306-311).
IEEE DOI 0602
BibRef

Spirito, M., Regazzoni, C.S., Marcenaro, L.,
Automatic detection of dangerous events for underground surveillance,
AVSBS05(195-200).
IEEE DOI 0602
BibRef

Regazzoni, C.S.[Carlo S.],
Emphatic human interaction analysis for cognitive environments,
ARTEMIS10(1-2).
DOI Link 1111
BibRef

Sacchi, C., Regazzoni, C.S., Vernazza, G.,
A neural network-based image processing system for detection of vandal acts in unmanned railway environments,
CIAP01(529-534).
WWW Link. 0210
BibRef

Seyve, C.,
Metro railway security algorithms with realworld experience adapted to the RATP dataset,
AVSBS05(177-182).
IEEE DOI 0602
BibRef

Shashua, A., Gdalyahu, Y., Hayun, G.,
Pedestrian detection for driving assistance systems: Single-frame classification and system level performance,
IVS04(1-6).
WWW Link. 0411
BibRef

Tons, M., Doerfler, R., Meinecke, M.M., Obojski, M.A.,
Radar sensors and sensor platform used for pedestrian protection in the EC-funded project SAVE-U,
IVS04(813-818).
WWW Link. 0411
BibRef

Sakamoto, Y., Aoki, M.,
Street model with multiple movable panels for pedestrian environment analysis,
IVS04(790-795).
WWW Link. 0411
BibRef

Grubb, G., Zelinsky, A., Nilsson, L., Rilbe, M.,
3D vision sensing for improved pedestrian safety,
IVS04(19-24).
WWW Link. 0411
BibRef

Kim, J.W.[Jae-Won], Choi, K.S.[Kang-Sun], Choi, B.D.[Byeong-Doo], Lee, J.Y.[Jae-Yong], Ko, S.J.[Sung-Jea],
Real-Time System for Counting the Number of Passing People Using a Single Camera,
DAGM03(466-473).
Springer DOI 0310
BibRef

Yang, D.B., Gonzalez-Banos, H.H.,
Counting people in crowds with a real-time network of simple image sensors,
ICCV03(122-129).
IEEE DOI 0311
BibRef

Bescos, J., Menendez, J.M., Garcia, N.,
DCT based segmentation applied to a scalable zenithal people counter,
ICIP03(III: 1005-1008).
IEEE DOI 0312
BibRef

Pece, A.E.C.,
From Cluster Tracking to People Counting,
PETS02(9-17). 0207
BibRef

Paragios, N.[Nikos], Ramesh, V.[Visvanathan],
A MRF-based Approach for Real-Time Subway Monitoring,
CVPR01(I:1034-1040).
IEEE DOI 0110
Pedestrian monitoring. BibRef

Shao, H.[Hui], Li, L.Y.[Li-Yuan], Xiao, P.[Ping], Leung, M.K.H.[Maylor K. H.],
ELEVIEW An Active Elevator Video Surveillance System,
HUMO00(67-72).
IEEE Top Reference. 0010
BibRef

Beymer, D.J.[David J.],
Person Counting Using Stereo,
HUMO00(127-134).
IEEE Top Reference. 0010
BibRef

Yoshida, D.[Daisuke], Terada, K.[Kenji], Oe, S.[Shun'ichiro], Yamaguchi, J.[Jun'ichi],
A method of Counting the Passing People by using the Stereo Images,
ICIP99(II:338-342).
IEEE DOI BibRef 9900

Terada, K., Kurokawa, N.,
A Method of Counting the Passing People by Using the Method of the Template Matching,
MVA98(xx-yy). BibRef 9800

Aubert, D.,
Passengers queue length measurement,
CIAP99(1132-1135).
IEEE DOI 9909
BibRef

Prassler, E., Scholz, J., Elfes, A.,
Tracking People in a Railway Station during Rush-Hour,
CVS99(162 ff.).
Springer DOI 0209
BibRef

Tsuchikawa, M., Sato, A., Koike, H., Tomono, A.,
A Moving Object Extraction Method Robust Against Illumination Level Changes for a Pedestrian Counting System,
SCV95(563-568).
IEEE DOI Application, Counting. Nippon Telegraph and Telephone Corp. Subtraction texhnique. Over a long sequence. BibRef 9500

Sato, A., Mase, K., Tomono, A., Ishii, K.,
Pedestrian Counting System Robust Against Illumination Changes,
SPIE(2094), 1993, pp. XX-YY. BibRef 9300

Khoudour, L., Deparis, J.P., Bruyelle, J.L., Cabestaing, F., Aubert, D., Bouchafa, S., Velastin, S.A., Vicencio-Silva, M.A., Wherett, M.,
Project CROMATICA,
CIAP97(II: 757-764).
Springer DOI 9709
Crowd density using flow. BibRef

Remagnino, P., Baumberg, A.M., Grove, T., Hogg, D.C., Tan, T.N., Worrall, A.D., Baker, K.D.,
An Integrated Traffic and Pedestrian Model-Based Vision System,
BMVC97(xx-yy).
HTML Version. 0209
BibRef

Rossi, M., and Bozzoli, A.,
Tracking and Counting Moving People,
ICIP94(III: 212-216).
IEEE DOI 9411
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Crosswalk Detection, Zebra Crossings .


Last update:Sep 18, 2017 at 11:34:11