16.7.4.2.3 Motion Based Human Detection, Spatio-Temporal Analysis, Pedestrians

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

Viola, P.[Paul], Jones, M.J.[Michael J.], Snow, D.[Daniel],
Detecting Pedestrians Using Patterns of Motion and Appearance,
IJCV(63), No. 2, July 2005, pp. 153-161.
Springer DOI 0501
BibRef
Earlier: ICCV03(734-741).
IEEE DOI 0311
Award, Marr Prize. BibRef

Foresti, G.L., Micheloni, C., Piciarelli, C.,
Detecting moving people in video streams,
PRL(26), No. 14, 15 October 2005, pp. 2232-2243.
Elsevier DOI 0510
See also Trajectory-Based Anomalous Event Detection. BibRef

Liu, Y.Z.[Ya-Zhou], Chen, X.L.[Xi-Lin], Yao, H.X.[Hong-Xun], Cui, X.Y.[Xin-Yi], Liu, C.[Chaoran], Gao, W.[Wen],
Contour-motion feature (CMF): A space-time approach for robust pedestrian detection,
PRL(30), No. 2, 15 January 2009, pp. 148-156,.
Elsevier DOI 0804
Contour-motion feature; Space-time analysis; Pedestrian detection; Human activity analysis; Event analysis; 3D Haar filter BibRef

Liu, Y.Z.[Ya-Zhou], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin], Heikkila, J.[Janne], Gao, W.[Wen], Pietikainen, M.[Matti],
Spatial-Temporal Granularity-Tunable Gradients Partition (STGGP) Descriptors for Human Detection,
ECCV10(I: 327-340).
Springer DOI 1009
BibRef

Liu, Y.Z.[Ya-Zhou], Heikkila, J.[Janne],
Isotropic Granularity-tunable gradients partition (IGGP) descriptors for human detection,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Liu, Y.Z.[Ya-Zhou], Shan, S.G.[Shi-Guang], Zhang, W.C.[Wen-Chao], Chen, X.L.[Xi-Lin], Gao, W.[Wen],
Granularity-tunable gradients partition (GGP) descriptors for human detection,
CVPR09(1255-1262).
IEEE DOI 0906
Hough space descriptors. Spatial and statistical properties. See also Fea-Accu cascade for face detection. BibRef

Pang, J.B.[Jun-Biao], Huang, Q.M.[Qing-Ming], Jiang, S.Q.[Shu-Qiang], Gao, W.[Wen],
Pedestrian detection via logistic multiple instance boosting,
ICIP08(1464-1467).
IEEE DOI 0810
BibRef

Zhang, J.G.[Jian-Guo], Gong, S.G.[Shao-Gang],
People detection in low-resolution video with non-stationary background,
IVC(27), No. 4, 3 March 2009, pp. 437-443.
Elsevier DOI 0804
Visual surveillance; People detection; Bayesian fusion; Long-term motion; AdaBoost BibRef

Zhang, J.G.[Jian-Guo], Gong, S.G.[Shao-Gang],
Action categorization with modified hidden conditional random field,
PR(43), No. 1, January 2010, pp. 197-203,.
Elsevier DOI 0909
Action recognition; Graph model; Hidden conditional random field; Optimum learning BibRef

Zhang, J.G.[Jian-Guo], Gong, S.G.[Shao-Gang],
Action categorization by structural probabilistic latent semantic analysis,
CVIU(114), No. 8, August 2010, pp. 857-864.
Elsevier DOI 1007
Action categorization; pLSA; Structural pLSA; Local shape context BibRef

Jo, Y.G.[Young-Gwan], Nam, W.H.[Woon-Hyun], Han, J.H.[Joon-Hee],
Pedestrian Segmentation From Uncalibrated Monocular Videos Using a Projection Map,
SPLetters(16), No. 7, July 2009, pp. 604-607.
IEEE DOI 0905
See also Object handoff between uncalibrated views without planar ground assumption. BibRef

Mucientes, M.[Manuel], Bugarin, A.[Alberto],
People detection through quantified fuzzy temporal rules,
PR(43), No. 4, April 2010, pp. 1441-1453.
Elsevier DOI 1002
People detection; Spatio-temporal pattern; Fuzzy temporal rules; Mobile robotics; Evolutionary algorithms BibRef

Zeng, B.[Bobo], Wang, G.J.[Gui-Jin], Lin, X.G.[Xing-Gang], Liu, C.X.[Chun-Xiao],
A Real-Time Human Detection System for Video,
IEICE(E95-D), No. 7, July 2012, pp. 1979-1988.
WWW Link. 1208
BibRef

Cao, T.P.[Tam Phuong], Elton, D.[Darrell], Deng, G.[Guang],
Fast buffering for FPGA implementation of vision-based object recognition systems,
RealTimeIP(7), No. 3, September 2012, pp. 173-183.
WWW Link. 1208
BibRef
Earlier: A1, A3, A2:
Fast Vision-Based Object Recognition Using Combined Integral Map,
CVS09(445-454).
Springer DOI 0910
BibRef

Cao, T.P.[Tam Phuong], Deng, G.[Guang], Mulligan, D.[David],
Implementation of real-time pedestrian detection on FPGA,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Borges, P.V.K.,
Pedestrian Detection Based on Blob Motion Statistics,
CirSysVideo(23), No. 2, February 2013, pp. 224-235.
IEEE DOI 1301
BibRef

Vinicius, P., Borges, P.V.K.,
Blob Motion Statistics for Pedestrian Detection,
DICTA11(442-447).
IEEE DOI 1205
BibRef

Zhang, H.B.[Hong-Bo], Li, S.Z.[Shao-Zi], Su, S.Z.[Song-Zhi], Chen, S.Y.[Shu-Yuan],
Selecting Effective and Discriminative Spatio-Temporal Interest Points for Recognizing Human Action,
IEICE(E96-D), No. 8, August 2013, pp. 1783-1792.
WWW Link. 1308
BibRef

Xie, Y.F.[Yao-Fang], Su, S.Z.[Song-Zhi], Li, S.Z.[Shao-Zi],
A pedestrian classification method based on transfer learning,
IASP10(420-425).
IEEE DOI 1004
BibRef

Su, S.Z.[Song-Zhi], Chen, S.Y.[Shu-Yuan], Li, S.Z.[Shao-Zi], Duh, D.J.[Der-Jyh],
Structured Local Edge Pattern Moment for pedestrian detection,
IASP10(556-560).
IEEE DOI 1004
BibRef

Miseikis, J., Borges, P.V.K.,
Joint Human Detection From Static and Mobile Cameras,
ITS(16), No. 2, April 2015, pp. 1018-1029.
IEEE DOI 1504
Cameras BibRef

Dohi, K.[Keisuke], Negi, K.[Kazuhiro], Shibata, Y.[Yuichiro], Oguri, K.[Kiyoshi],
FPGA Implementation of Human Detection by HOG Features with AdaBoost,
IEICE(E96-D), No. 8, August 2013, pp. 1676-1684.
WWW Link. 1308
BibRef

Crooks, A.[Andrew], Croitoru, A.[Arie], Lu, X.[Xu], Wise, S.[Sarah], Irvine, J.M.[John M.], Stefanidis, A.[Anthony],
Walk This Way: Improving Pedestrian Agent-Based Models through Scene Activity Analysis,
IJGI(4), No. 3, 2015, pp. 1627.
DOI Link 1511
BibRef

Bhole, C.[Chetan], Pal, C.[Christopher],
Fully automatic person segmentation in unconstrained video using spatio-temporal conditional random fields,
IVC(51), No. 1, 2016, pp. 58-68.
Elsevier DOI 1606
BibRef
Earlier:
Automated person segmentation in videos,
ICPR12(3672-3675).
WWW Link. 1302
Person segmentation BibRef

Noaman, R.A.K.[Redwan A.K.], Ali, M.A.M.[Mohd Alauddin Mohd], Zainal, N.[Nasharuddin],
Enhancing pedestrian detection using optical flow for surveillance,
IJCVR(7), No. 1/2, 2017, pp. 35-48.
DOI Link 1701
BibRef

Wang, Y.[Yi], Piérard, S.[Sébastien], Su, S.Z.[Song-Zhi], Jodoin, P.M.[Pierre-Marc],
Improving pedestrian detection using motion-guided filtering,
PRL(96), No. 1, 2017, pp. 106-112.
Elsevier DOI 1709
BibRef
Earlier:
Nonlinear Background Filter to Improve Pedestrian Detection,
SBMI15(535-543).
Springer DOI 1511
Pedestrian, detection BibRef


Kilicarslan, M., Zheng, J.Y., Raptis, K.,
Pedestrain detection from motion,
ICPR16(1857-1863)
IEEE DOI 1705
Automobiles, Cameras, Dynamics, Image edge detection, Legged locomotion, Shape, Trajectory, driving video, pedestrian detection, pedestrian motion, spatial-temporal filtering, tracking BibRef

Seguin, G.[Guillaume], Bojanowski, P.[Piotr], Lajugie, R.[Rémi], Laptev, I.[Ivan],
Instance-Level Video Segmentation from Object Tracks,
CVPR16(3678-3687)
IEEE DOI 1612
BibRef

González, A.[Alejandro], Vázquez, D.[David], Ramos, S.[Sebastian], López, A.M.[Antonio M.], Amores, J.[Jaume],
Spatiotemporal Stacked Sequential Learning for Pedestrian Detection,
IbPRIA15(3-12).
Springer DOI 1506
BibRef

González, A.[Alejandro], Villalonga, G.[Gabriel], Ros, G.[German], Vázquez, D.[David], López, A.M.[Antonio M.],
3D-Guided Multiscale Sliding Window for Pedestrian Detection,
IbPRIA15(560-568).
Springer DOI 1506
BibRef

Hariyono, J.[Joko], Jo, K.H.[Kang-Hyun],
Detection of pedestrian crossing road,
ICIP15(4585-4588)
IEEE DOI 1512
Pedestrian detection; location classification; optical flow BibRef

Mao, Y.X.[Yun-Xiang], Yin, Z.Z.[Zhao-Zheng],
Training a Scene-Specific Pedestrian Detector Using Tracklets,
WACV15(170-176)
IEEE DOI 1503
Cameras BibRef

Zhu, J.J.[Jie-Jie], Javed, O.[Omar], Liu, J.G.[Jin-Gen], Yu, Q.[Qian], Cheng, H.[Hui], Sawhney, H.[Harpreet],
Pedestrian Detection in Low-Resolution Imagery by Learning Multi-scale Intrinsic Motion Structures (MIMS),
CVPR14(3510-3517)
IEEE DOI 1409
BibRef

Brown, L.M.[Lisa M.], Feris, R.[Rogerio], Pankanti, S.[Sharathchandra],
Temporal Non-maximum Suppression for Pedestrian Detection Using Self-Calibration,
ICPR14(2239-2244)
IEEE DOI 1412
Accuracy BibRef

Al Harbi, N.[Nouf], Gotoh, Y.[Yoshihiko],
Spatio-temporal Human Body Segmentation from Video Stream,
CAIP13(78-85).
Springer DOI 1308
BibRef

Al Ghamdi, M.[Manal], Gotoh, Y.[Yoshihiko],
Manifold Matching with Application to Instance Search Based on Video Queries,
ICISP14(477-486).
Springer DOI 1406
BibRef
Earlier:
Spatio-temporal Manifold Embedding for Nearly-Repetitive Contents in a Video Stream,
CAIP13(70-77).
Springer DOI 1308
BibRef

Al Ghamdi, M.[Manal], Al Harbi, N.[Nouf], Gotoh, Y.[Yoshihiko],
Spatio-temporal Video Representation with Locality-Constrained Linear Coding,
ARTEMIS12(III: 101-110).
Springer DOI 1210
BibRef

Yang, Y.[Yang], Shu, G.[Guang], Shah, M.[Mubarak],
Semi-supervised Learning of Feature Hierarchies for Object Detection in a Video,
CVPR13(1650-1657)
IEEE DOI 1309
Object detection; deep learning; feature learning; video analysis. Learn video-specific features. Person and horse detection application. BibRef

Hahnle, M.[Michael], Saxen, F.[Frerk], Hisung, M.[Matthias], Brunsmann, U.[Ulrich], Doll, K.[Konrad],
FPGA-Based Real-Time Pedestrian Detection on High-Resolution Images,
ECVW13(629-635)
IEEE DOI 1309
FPGA BibRef

De Smedt, F.[Floris], Hulens, D.[Dries], Goedeme, T.[Toon],
On-board real-time tracking of pedestrians on a UAV,
ECVW15(1-8)
IEEE DOI 1510
Approximation methods BibRef

De Smedt, F.[Floris], van Beeck, K.[Kristof], Tuytelaars, T.[Tinne], Goedeme, T.[Toon],
Pedestrian Detection at Warp Speed: Exceeding 500 Detections per Second,
ECVW13(622-628)
IEEE DOI 1309
GPU optimization;Object detection;Vision application BibRef

Kawanishi, Y., Deguchi, D.[Daisuke], Ide, I.[Ichiro], Murase, H.[Hiroshi], Fujiyoshi, H.,
Misclassification tolerable learning for robust pedestrian orientation classification,
ICPR16(486-491)
IEEE DOI 1705
Accidents, Cameras, Legged locomotion, Optimization, Sensors, Support vector machines, Training BibRef

Wakayama, M.[Masashi], Deguchi, D.[Daisuke], Doman, K.[Keisuke], Ide, I.[Ichiro], Murase, H.[Hiroshi], Tamatsu, Y.[Yukimasa],
Estimation of the human performance for pedestrian detectability based on visual search and motion features,
ICPR12(1940-1943).
WWW Link. 1302
BibRef

Jin, X.[Xuyuan], Heinrich, A.[Adrienne], Shan, C.F.[Cai-Feng], de Haan, G.[Gerard],
Shared-bed person segmentation based on motion estimation,
ICIP12(137-140).
IEEE DOI 1302
BibRef

Park, W.J.[Won-Jae], Kim, D.H.[Dae-Hwan], Suryanto, Lyuh, C.G.[Chun-Gi], Roh, T.M.[Tae Moon], Ko, S.J.[Sung-Jea],
Fast human detection using selective block-based HOG-LBP,
ICIP12(601-604).
IEEE DOI 1302
BibRef

Dollár, P.[Piotr], Appel, R.[Ron], Kienzle, W.[Wolf],
Crosstalk Cascades for Frame-Rate Pedestrian Detection,
ECCV12(II: 645-659).
Springer DOI 1210
BibRef

Chen, W.[Wei], Yang, Q.X.[Quan-Xi], Lin, K.W.[Ke-Wei], Wang, S.Y.[Sheng-Yu], Huang, C.L.[Chung-Lin],
Human and car identification using motion vector in H.264 compressed video,
VCIP11(1-4).
IEEE DOI 1201
Find moving objects, then classify. BibRef

Maki, A.[Atsuto], Seki, A.[Akihito], Watanabe, T.[Tomoki], Cipolla, R.[Roberto],
Co-occurrence flow for pedestrian detection,
ICIP11(1889-1892).
IEEE DOI 1201
BibRef

Galasso, F.[Fabio], Iwasaki, M.[Masahiro], Nobori, K.[Kunio], Cipolla, R.[Roberto],
Spatio-temporal clustering of probabilistic region trajectories,
ICCV11(1738-1745).
IEEE DOI 1201
for pedestrian trajectories BibRef

del Bimbo, A.[Alberto], Lisanti, G.[Giuseppe], Masi, I.[Iacopo], Pernici, F.[Federico],
Person Detection Using Temporal and Geometric Context with a Pan Tilt Zoom Camera,
ICPR10(3886-3889).
IEEE DOI 1008
BibRef

Yamauchi, Y.[Yuji], Fujiyoshi, H.[Hironobu], Hwang, B.W.[Bon-Woo], Kanade, T.[Takeo],
People detection based on co-occurrence of appearance and spatiotemporal features,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Venkatraman, D., Makur, A.,
Shadow-less segmentation of moving humans from surveillance video sequences,
ICARCV08(1317-1322).
IEEE DOI 1109
BibRef

Beleznai, C.[Csaba], Rauter, M.[Michael], Shao, D.[Dan],
Real-time human detection using fast contour template matching for visual surveillance,
AVSBS11(514).
IEEE DOI 1111
AVSS2011 demo session BibRef

Kim, D.H.[Dae-Hwan], Kim, D.J.[Dai-Jin],
Self-occlusion handling for human body motion tracking from 3D ToF image sequence,
3DVP10(57-62).
DOI Link 1111
BibRef

Garcia-Martin, A., Hauptmann, A.G., Martinez, J.M.,
People detection based on appearance and motion models,
AVSBS11(256-260).
IEEE DOI 1111
BibRef

Mayya, M.[Mohammad], Zarka, N.[Nizar], Alkadi, M.S.[Mohammad Soubhi],
Embedded system for real-time human motion detection,
IPTA10(523-528).
IEEE DOI 1007
BibRef

Cheung, S.M.[Siu-Ming], Moon, Y.S.[Yiu-Sang],
Detection of Approaching Pedestrians from a Distance Using Temporal Intensity Patterns,
MVA09(354-).
PDF File. 0905
BibRef

Figueira, D.[Dario], Moreno, P.[Plinio], Bernardino, A.[Alexandre], Gaspar, J.[José], Santos-Victor, J.[José],
Optical Flow Based Detection in Mixed Human Robot Environments,
ISVC09(I: 223-232).
Springer DOI 0911
Optical flow features to distinguish between humans and robots. See also Re-identification of Visual Targets in Camera Networks: A Comparison of Techniques. BibRef

Ding, W.R.[Wen-Rui], Li, H.G.[Hong-Guang], Jiang, Z.[Zhe], Li, X.J.[Xin-Jun],
Unsupervised Spatio-Temporal Multi-Human Detection and Recognition in Complex Scene,
CISP09(1-5).
IEEE DOI 0910
BibRef

Habe, H.[Hitoshi], Nakagawa, H.[Hidehito], Kidode, M.[Masatsugu],
Efficient acquisition of human existence priors from motion trajectories,
VCL-ViSU09(85-91).
IEEE DOI 0906
Person detection based on prior trajectories. BibRef

Goel, D.[Dhiraj], Chen, T.H.[Tsu-Han],
Pedestrian Detection Using Global-Local Motion Patterns,
ACCV07(I: 220-229).
Springer DOI 0711
BibRef
And:
Real-Time Pedestrian Detection using Eigenflow,
ICIP07(III: 229-232).
IEEE DOI 0709
BibRef

Dalal, N.[Navneet], Triggs, B.[Bill], Schmid, C.[Cordelia],
Human Detection Using Oriented Histograms of Flow and Appearance,
ECCV06(II: 428-441).
Springer DOI 0608
BibRef

Haga, T., Sumi, K., Yagi, Y.,
Human detection in outdoor scene using spatio-temporal motion analysis,
ICPR04(IV: 331-334).
IEEE DOI 0409
BibRef

Wöhler, C., Kreßel, U., Anlauf, J.K.,
Pedestrian Recognition by Classification of Image Sequences: Global Approaches vs. Local Spatio-temporal Processing,
ICPR00(Vol II: 540-544).
IEEE DOI 0009
See also Real-time object recognition on image sequences with the adaptable time delay neural network algorithm applications for autonomous vehicles. See also Time Delay Neural Network Algorithm for Estimating Image-Pattern Shape and Motion, A. BibRef

Heisele, B.[Bernd], Wöhler, C.[Christian],
Motion-Based Recognition of Pedestrians,
ICPR98(Vol II: 1325-1330).
IEEE DOI 9808
BibRef

Vannoorenberghe, P.[Patrick], Motamed, C.[Cina], Blosseville, J.M.[Jean-Marc], Postaire, J.G.[Jack-Gérard],
Automatic pedestrian recognition using real-time motion analysis,
CIAP97(II: 493-500).
Springer DOI 9709
BibRef

Kinzel, W., Dickmanns, E.D.,
Moving Humans Recognition Using Spatio-Temporal Models,
ISPRS92(xx). BibRef 9200

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Human Detection, People Detection, Pedestrians, Using Depth, Stereo .


Last update:Sep 25, 2017 at 16:36:46