16.6 Tracking of Moving Objects and Matching in Sequences

Chapter Contents (Back)
Sequences. Tracking. Motion, Tracking. There should be some mention of the much older basic tracking effort (e.g. spots, etc.).

CVonline: Motion, Tracking and Time Sequence Analysis,
CV-OnlineJuly 2001.
HTML Version. Survey, Motion. Survey, Tracking. BibRef 0107

Hopkins 155,
Motion Dataset Online2007.
WWW Link. Dataset, Motion. Testing feature based motion segmentation algorithms. See also Johns Hopkins University. BibRef 0700

Martin, W.N., and Aggarwal, J.K.,
Computer Analysis of Dynamic Scenes Containing Curvilinear Figures,
PR(11), No. 3, 1979, pp. 169-178.
Elsevier DOI Represent the curves in polar form - arc length vs. angle. From these there are pieces of curves, match the curves. Assume that the scenes are motion sequences so that the changes are position and occlusions / separations. See also Volumetric Descriptions of Objects from Multiple Views. BibRef 7900

Martin, W.N., and Aggarwal, J.K.,
Occluding Contours in Dynamic Scenes,
PRIP81(189-192). BibRef 8100

Aggarwal, J.K., and Martin, W.N.,
Analyzing Dynamic Scenes Containing Moving Objects,
ISA81(Ch 6). BibRef 8100

Aggarwal, J.K., and Duda, R.O.,
Computer Analysis of Moving Polygonal Images,
TC(24), No. 10, October 1975, pp. 966-976. BibRef 7510 CMetImAly77(271-282). Motion, Tracking. Motivated by cloud motions assumes: properly registered, clouds not rapidly changing, and 1 layer at a time. Information in joint motion - to avoid problems and obtain generality: idealized model no distinguishing features of the planes (image is union of several planes.). Given a sequence find linear and angular velocities and decompose scene into component figures. Noise free; pair vertices in 2 images - using true and false vertices; use info from previous image; acute vertex => "true" vertex, i.e., on an object; obtuse => any kind; cluster on velocity of true vertices; heuristic: no guarantee that matches are globally optimal; no processes for backtracking. BibRef

Chow, W.K., and Aggarwal, J.K.,
Computer Analysis of Planar Curvilinear Moving Images,
TC(26), No. 2, February 1977, pp. 179-185. Eliminates assumptions in Aggarwal & Duda ( See also Computer Analysis of Moving Polygonal Images. ), i.e., - curved objects, multiple topological changes, but no holes; all objects known before motion analysis; no occlusion for first 2 views; white on black background objects; noise, stable velocity, i.e., low acceleration; heterogeneous collection of objects; edges; descriptors - invariant to rotation and translation area, modified principal axes (major/minor axes); matches new image with current model to get update model, if fails then match with prediction; extension match boundaries rather than descriptors. BibRef 7702

Roach, J.W., and Aggarwal, J.K.,
Computer Tracking of Objects Moving in Space,
PAMI(1), No. 2, April 1979, pp. 127-135. BibRef 7904
Earlier:
Computer Tracking of Three Dimensional Objects,
PRAI-78(7-9). Detect movement of 3-D convex blocks in 2-D images. Use evidence from T-junctions for occlusions. BibRef

Aggarwal, J.K., Davis, L.S., and Martin, W.N.,
Correspondence Processes in Dynamic Scene Analysis,
PIEEE(69), No. 5, May 1981, pp. 562-572. BibRef 8105

Thompson, W.B., Lechleider, P., and Stuck, E.R.,
Detecting Moving Objects Using the Rigidity Constraint,
PAMI(15), No. 2, February 1993, pp. 162-166.
IEEE DOI Not really tracking, more motion detection. Compute the motion of the camera compared to the background. Moving objects are the points that do not correspond. BibRef 9302

Nichol, D.[David], Fiebig, M.[Merrilyn],
Image Segmentation and Matching Using the Binary Object Forest,
IVC(9), No. 3, June 1991, pp. 139-149.
Elsevier DOI BibRef 9106

Nichol, D.[David], Fiebig, M.[Merrilyn],
Tracking Multiple Moving Objects by Binary Object Forest Segmentation,
IVC(9), No. 6, December 1991, pp. 362-371.
Elsevier DOI BibRef 9112

Lowe, D.G.[David G.],
Robust Model-Based Motion Tracking Through the Integration of Search and Estimation,
IJCV(8), No. 2, August 1992, pp. 113-122.
Springer DOI BibRef 9208
And: UBCTR-92-11, May 1992. Handle both measurement and motion errors that occur in following the sequence. BibRef

Cox, I.J.,
A Review of Statistical Data Association Techniques for Motion Correspondence,
IJCV(10), No. 1, February 1993, pp. 53-66.
Springer DOI Survey, Tracking. Techniques that came from target tracking work. BibRef 9302

Stuller, J.A.[John A.], and Krishnamurthy, G.[Gaplan],
Kalman Filter Formulation of Low-Level Television Image Motion Estimation,
CVGIP(21), No. 2, February 1983, pp. 169-204.
Elsevier DOI Kalman Filter. BibRef 8302

Burl, J.B.,
A Reduced Order Extended Kalman Filter for Sequential Images Containing a Moving Object,
IP(2), No. 3, July 1993, pp. 285-295.
IEEE DOI BibRef 9307

Stuller, J.A., and Netravali, A.N.,
Transform Domain Motion Estimation,
Bell System Tech.(58), September, 1979, pp. 1673-1702. BibRef 7909

Netravali, A.N.[Arun N.], Stuller, J.A.[John A.],
Motion estimation and encoding of video signals in the transform domain,
US_Patent4,245,248, Jan 13, 1981
WWW Link. BibRef 8101

Nosler, J.C.[John C.],
Electro-optical position-monitoring apparatus with tracking detector,
US_Patent4,269,512, May 26, 1981
WWW Link. BibRef 8105

Cowart, A.E.[Alan E.], Snyder, W.E.[Wesley E.], and Ruedger, W.H.[W. Howard],
The Detection of Unresolved Targets Using the Hough Transform,
CVGIP(21), No. 2, February 1983, pp. 222-238.
Elsevier DOI Hough, Motion. BibRef 8302

Mirmehdi, M., Ellis, T.J.,
Parallel Approach to Tracking Edge Segments in Dynamic Scenes,
IVC(11), No. 1, January-February 1993, pp. 35-48.
Elsevier DOI Parallel processors (transputers) applied to tracking problem. BibRef 9301

Ellis, T.J., Mirmehdi, M., and Dowling, G.R.,
Tracking Image Features Using a Parallel Computational Model,
SPIE(1708), Applications of Artificial Intelligence X: Machine vision and Robots, 1992, pp. 172-183. Implementation using transputers. BibRef 9200

Deffontaines, T.[Thierry],
Method for identifying objects in motion, in particular vehicles, and systems for its implementation,
US_Patent5,083,200, 01/21/1992.
HTML Version. BibRef 9201

Zhang, Z.Y.[Zheng-You],
Token Tracking in a Cluttered Scene,
IVC(12), No. 2, March 1994, pp. 110-120.
Elsevier DOI BibRef 9403
And: INRIARR-2072, October 1993. BibRef
Earlier:
Strategies for Tracking Tokens in a Cluttered Scene,
BMVC93(I. 205-216).
PDF File. Uses a beam search. BibRef

Snijder, H.P.[Henk Philip], van Leeuwen, C.[Cees],
A Minimal Architecture for Detecting Object Location and Motion,
PR(27), No. 11, November 1994, pp. 1463-1473.
Elsevier DOI BibRef 9411

Sharp, N.G.[Nigel G.], Hancock, E.R.[Edwin R.],
Feature Tracking by Multiframe Relaxation,
IVC(13), No. 8, October 1995, pp. 637-644.
Elsevier DOI BibRef 9510
Earlier: BMVC94(xx-yy).
PDF File. 9409
BibRef

Bruckstein, A.M., Holt, R.J., Netravali, A.N.,
How to Catch a Crook,
JVCIR(5), 1994, pp. 273-281. BibRef 9400

Bruckstein, A.M., Holt, R.J., Netravali, A.N.,
How to Track a Flying Saucer,
JVCIR(7), No. 2, June 1996, pp. 196-204. 9607
BibRef

Choate, W.C.[William Clay], Talluri, R.K.[Rajendra K.],
Method of inferring sensor attitude through multi-feature tracking,
US_Patent5,647,015, Jul 8, 1997
WWW Link. BibRef 9707
And: US_Patent5,870,486, Feb 9, 1999
WWW Link. BibRef
And: A2, A1:
Target Tracking and Range Estimation Using an Image Sequence,
WACV92(84-91).
WWW Link. BibRef

Habib, A.,
Motion Parameter Estimation by Tracking Stationary 3-Dimensional Straight Lines in Image Sequences,
PandRS(53), No. 3, June 1998, pp. 174-182. 9807
BibRef

Zatelli, P.,
Measurement and Tracking of Circle Centers for Geotechnic Applications,
PandRS(53), No. 3, June 1998, pp. 183-191. 9807
BibRef

Heimes, F., Nagel, H.H.,
Real Time Tracking of Intersections in Image Sequences of a Moving Camera,
EngAAI(11), No. 2, April 1998, pp. 215-227. 9807
BibRef

Jung, S.K., Wohn, K.Y.,
A Model Based 3-D Tracking of Rigid Objects from a Sequence of Multiple Perspective Views,
PRL(19), No. 5-6, April 1998, pp. 499-512. 9808
BibRef

Sanders-Reed, J.N.[John N.],
Maximum Likelihood Detection of Unresolved Moving Targets,
AeroSys(34), No.3, July, 1998, pp. xx-yy.
WWW Link. Faint target detection and tracking. BibRef 9807

Toyama, K.[Kentaro], Hager, G.D.[Gregory D.],
Incremental Focus of Attention for Robust Vision-Based Tracking,
IJCV(35), No. 1, November 1999, pp. 45-63.
DOI Link BibRef 9911
Earlier:
Incremental Focus of Attention for Robust Visual Tracking,
CVPR96(189-195).
IEEE DOI Tracking.
HTML Version. And
PS File. BibRef
Earlier:
Tracker Fusion for Robustness in Visual Feature Tracking,
SPIE(2569), pp. 38-49. Photonics East, October 1995.
PS File. Code, Tracking. Code:
WWW Link. BibRef

Toyama, K.[Kentaro],
Handling Tradeoffs Between Precision and Robustness with Incremental Focus of Attention for Visual Tracking,
AAAI-Fall96(142-147). Symposium on Flexible Computation.
HTML Version. And
PS File. BibRef 9600

Hu, X.P.[Xiao-Ping], Takamura, J.[Jun], Hall, M.[Mark],
Video object tracking method for interactive multimedia applications,
US_Patent5,867,584, Feb 2, 1999
WWW Link. BibRef 9902

Erdem, Ç.E., Tekalp, A.M., Sankur, B.,
Video object tracking with feedback of performance measures,
CirSysVideo(13), No. 4, April 2003, pp. 310-324.
IEEE Abstract. 0301
BibRef
Earlier: A1, A3, A2:
Non-Rigid Object Tracking using Performance Evaluation Measures as Feedback,
CVPR01(II:323-330).
IEEE DOI 0110
BibRef

Erdem, C.E.[Cigdem Eroglu],
Video object segmentation and tracking using region-based statistics,
SP:IC(22), No. 10, November 2007, pp. 891-905.
Elsevier DOI 0711
Object tracking; Active contours; Histogram matching; Curve evolution; Defocus; Selective focus BibRef

Erdem, C.E.[C. Eroglu], Sankur, B., Tekalp, A.M.,
Performance Measures for Video Object Segmentation and Tracking,
IP(13), No. 7, July 2004, pp. 937-951.
IEEE DOI 0406
BibRef
Earlier: A1, A3, A2:
Metrics for Performance Evaluation of Video Object Segmentation and Tracking Without Ground-truth,
ICIP01(II: 69-72).
IEEE DOI 0108
BibRef

Lin, C.F.[Ching-Fang],
Three-dimensional relative positioning and tracking using LDRI,
US_Patent6,677,941, Jan 13, 2004
WWW Link. BibRef 0401

Williams, O., Blake, A., Cipolla, R.,
Sparse Bayesian Learning for Efficient Visual Tracking,
PAMI(27), No. 8, August 2005, pp. 1292-1304.
IEEE Abstract. 0506
BibRef
Earlier:
A sparse probabilistic learning algorithm for real-time tracking,
ICCV03(353-360).
IEEE DOI 0311
BibRef

Jia, Z.[Zhen], Balasuriya, A.[Arjuna], Challa, S.[Subhash],
Vision Based Target Tracking for Autonomous Land Vehicle Navigation: A Brief Survey,
RPCS(2), No. 1, January 2009, pp. 32-42.
WWW Link. 1001
Survey, Tracking. BibRef

Maggio, E.[Emilio], Cavallaro, A.[Andrea],
Video Tracking: Theory and Practice,
WileyApril 2011 ISBN: 978-0-470-74964-7
HTML Version. Buy this book: Video Tracking: Theory and Practice 1010
BibRef

Nawaz, T.[Tahir], Poiesi, F.[Fabio], Cavallaro, A.[Andrea],
Measures of Effective Video Tracking,
IP(23), No. 1, January 2014, pp. 376-388.
IEEE DOI 1402
BibRef
And:
Assessing tracking assessment measures,
ICIP14(441-445)
IEEE DOI 1502
Area measurement object tracking BibRef

Mei, X.[Xue], Ling, H.B.[Hai-Bin],
Robust Visual Tracking and Vehicle Classification via Sparse Representation,
PAMI(33), No. 11, November 2011, pp. 2259-2272.
IEEE DOI 1110
BibRef
Earlier:
Robust Visual Tracking Using L1 Minimization,
ICCV09(1436-1443).
IEEE DOI
PDF File. 0909
See also Illumination Recovery From Image With Cast Shadows Via Sparse Representation. BibRef

Fan, H.[Heng], Ling, H.B.[Hai-Bin],
SANet: Structure-Aware Network for Visual Tracking,
DeepLearn-T17(2217-2224)
IEEE DOI 1709
Computational modeling, Computer vision, Feature extraction, Recurrent neural networks, Robustness, Target tracking, Visualization BibRef

Hong, Z.B.[Zhi-Bin], Wang, C.H.[Chao-Hui], Mei, X.[Xue], Prokhorov, D.[Danil], Tao, D.C.[Da-Cheng],
Tracking Using Multilevel Quantizations,
ECCV14(VI: 155-171).
Springer DOI 1408
BibRef

Hong, Z.B.[Zhi-Bin], Mei, X.[Xue], Prokhorov, D.[Danil], Tao, D.C.[Da-Cheng],
Tracking via Robust Multi-task Multi-view Joint Sparse Representation,
ICCV13(649-656)
IEEE DOI 1403
Multi-task; Multi-view; Outliers; Sparse Representation; Tracking BibRef

Easson, G., De Lozier, S., Momm, H.,
Estimating Speed and Direction of Small Dynamic Targets through Optical Satellite Imaging,
RS(2), No. 5, May 2010, pp. 1331-1347.
DOI Link 1203
BibRef

Salti, S., Cavallaro, A., di Stefano, L.[Luigi],
Adaptive Appearance Modeling for Video Tracking: Survey and Evaluation,
IP(21), No. 10, October 2012, pp. 4334-4348.
IEEE DOI 1209
BibRef

Salti, S.[Samuele], di Stefano, L.[Luigi],
On-line Support Vector Regression of the transition model for the Kalman filter,
IVC(31), No. 6-7, June-July 2013, pp. 487-501.
Elsevier DOI 1306
Adaptive transition model; Visual tracking; Support Vector Regression; Kalman filter; Interacting Multiple Models BibRef

Salti, S.[Samuele], Lanza, A., di Stefano, L.[Luigi],
Synergistic Change Detection and Tracking,
CirSysVideo(25), No. 4, April 2015, pp. 609-622.
IEEE DOI 1504
Bayes methods BibRef

Fan, J., Shen, X., Wu, Y.,
What Are We Tracking: A Unified Approach of Tracking and Recognition,
IP(22), No. 2, February 2013, pp. 549-560.
IEEE DOI 1302
BibRef

Ammari, H.[Habib], Boulier, T.[Thomas], Garnier, J.[Josselin],
Modeling Active Electrolocation in Weakly Electric Fish,
SIIMS(6), No. 1, 2013, pp. 285-321.
DOI Link 1304
BibRef

Ammari, H.[Habib], Boulier, T., Garnier, J.[Josselin], Kang, H.B.[Hyeon-Bae], Wang, H.,
Tracking of a Mobile Target Using Generalized Polarization Tensors,
SIIMS(6), No. 3, 2013, pp. 1477-1498.
DOI Link 1310
BibRef

Seo, J., Kim, S.D.,
Visual Target TRACTOR: Tracker and Detector,
CirSysVideo(25), No. 5, May 2015, pp. 761-775.
IEEE DOI 1505
Adaptation models BibRef

Granstrom, K., Natale, A., Braca, P., Ludeno, G., Serafino, F.,
Gamma Gaussian Inverse Wishart Probability Hypothesis Density for Extended Target Tracking Using X-Band Marine Radar Data,
GeoRS(53), No. 12, December 2015, pp. 6617-6631.
IEEE DOI 1512
geophysical techniques BibRef

Millefiori, L.M., Braca, P., Willett, P.,
Consistent Estimation of Randomly Sampled Ornstein-Uhlenbeck Process Long-Run Mean for Long-Term Target State Prediction,
SPLetters(23), No. 11, November 2016, pp. 1562-1566.
IEEE DOI 1609
covariance analysis BibRef

Vivone, G., Millefiori, L.M., Braca, P., Willett, P.,
Performance Assessment of Vessel Dynamic Models for Long-Term Prediction Using Heterogeneous Data,
GeoRS(55), No. 11, November 2017, pp. 6533-6546.
IEEE DOI 1711
Radar tracking, Synthetic aperture radar, Uncertainty, maritime surveillance, ornstein-Uhlenbeck (OU) process. BibRef

Gao, Y.[Yun], Zhou, H.[Hao], Zhang, X.J.[Xue-Jie],
Enhanced fast compressive tracking based on adaptive measurement matrix,
IET-CV(9), No. 6, 2015, pp. 857-863.
DOI Link 1512
compressed sensing BibRef

Elafi, I.[Issam], Jedra, M.[Mohamed], Zahid, N.[Noureddine],
Unsupervised detection and tracking of moving objects for video surveillance applications,
PRL(84), No. 1, 2016, pp. 70-77.
Elsevier DOI 1612
Particle filter BibRef

Gu, X.D.[Xiao-Dong], Huang, X.Y.[Xin-Yu], Tokuta, A.[Alade],
Multiscale spatially regularised correlation filters for visual tracking,
IET-CV(11), No. 3, April 2017, pp. 220-225.
DOI Link 1704
BibRef

Wang, X.[Xin], Shen, S.[Siqiu], Ning, C.[Chen], Zhang, Y.Z.[Yu-Zhen], Lv, G.F.[Guo-Fang],
Robust object tracking based on local discriminative sparse representation,
JOSA-A(34), No. 4, April 2017, pp. 533-544.
DOI Link 1704
Digital image processing BibRef

Bai, B.[Bendu], Li, Y.[Ying], Fan, J.L.[Jiu-Lun], Price, C.[Chris], Shen, Q.[Qiang],
Object tracking based on incremental Bi-2DPCA learning with sparse structure,
AppOpt(54), No. 10, 2015, pp. 2897-2907.
WWW Link. 1704
BibRef

Zeng, F., Huang, Z., Ji, Y.,
Discriminative Bag-of-Words-Based Adaptive Appearance Model for Robust Visual Tracking,
SPLetters(24), No. 6, June 2017, pp. 907-911.
IEEE DOI 1705
Adaptation models, Computational modeling, Deformable models, Indexes, Robustness, Signal processing algorithms, Visualization, Adaptive appearance model, discriminative bag-of-words (DBoW), visual, tracking BibRef

Danelljan, M.[Martin], Häger, G.[Gustav], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
Discriminative Scale Space Tracking,
PAMI(39), No. 8, August 2017, pp. 1561-1575.
IEEE DOI 1707
BibRef
Earlier:
Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking,
CVPR16(1430-1438)
IEEE DOI 1612
BibRef
Earlier:
Learning Spatially Regularized Correlation Filters for Visual Tracking,
ICCV15(4310-4318)
IEEE DOI 1602
BibRef
And:
Convolutional Features for Correlation Filter Based Visual Tracking,
VOT15(621-629)
IEEE DOI 1602
BibRef
And:
Coloring Channel Representations for Visual Tracking,
SCIA15(117-129).
Springer DOI 1506
BibRef
Earlier:
Accurate Scale Estimation for Robust Visual Tracking,
BMVC14(xx-yy).
HTML Version. 1410
Correlation, Decision support systems, Estimation, Robustness, Standards, Target tracking, Visualization, Visual tracking, correlation filters, scale, estimation Benchmark testing BibRef

Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael], van de Weijer, J.[Joost],
Adaptive Color Attributes for Real-Time Visual Tracking,
CVPR14(1090-1097)
IEEE DOI 1409
Adaptive Dimensionality Reduction BibRef

Gladh, S., Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
Deep motion features for visual tracking,
ICPR16(1243-1248)
IEEE DOI 1705
Feature extraction, Image color analysis, Optical imaging, Target tracking, Training, Visualization BibRef

Johnander, J.[Joakim], Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
DCCO: Towards Deformable Continuous Convolution Operators for Visual Tracking,
CAIP17(I: 55-67).
Springer DOI 1708
BibRef

Danelljan, M.[Martin], Robinson, A.[Andreas], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking,
ECCV16(V: 472-488).
Springer DOI 1611
BibRef

Chan, S.X.[Si-Xian], Zhou, X.L.[Xiao-Long], Li, J.W.[Jun-Wei], Chen, S.Y.[Sheng-Yong],
Adaptive Compressive Tracking based on Locality Sensitive Histograms,
PR(72), No. 1, 2017, pp. 517-531.
Elsevier DOI 1708
Compressive tracking BibRef

Wang, H.Q.[Hong-Qing], Xu, T.F.[Ting-Fa], Guo, J.[Jie], Rao, Z.T.[Zhi-Tao], Shi, G.K.[Guo-Kai],
Incremental subspace and probability mask constrained tracking in smart and autonomous systems,
PR(72), No. 1, 2017, pp. 473-483.
Elsevier DOI 1708
Smart and autonomous systems BibRef

Kang, W.J.[Wen-Jing], Liu, G.L.[Gong-Liang], Jia, M.[Min],
Adaptive correlation filters for robust object tracking,
PR(72), No. 1, 2017, pp. 484-493.
Elsevier DOI 1708
Adaptive correlation filter BibRef

Tran, A.[Antoine], Manzanera, A.[Antoine],
Mixing Hough and Color Histogram Models for Accurate Real-Time Object Tracking,
CAIP17(I: 43-54).
Springer DOI 1708
BibRef

Li, H., Wu, H., Zhang, H., Lin, S., Luo, X., Wang, R.,
Distortion-Aware Correlation Tracking,
IP(26), No. 11, November 2017, pp. 5421-5434.
IEEE DOI 1709
Context modeling, Correlation, Distortion, Target tracking, Training, distortion-aware, normed, correlation, response BibRef

Guo, Q., Feng, W., Zhou, C., Pun, C.M., Wu, B.,
Structure-Regularized Compressive Tracking With Online Data-Driven Sampling,
IP(26), No. 12, December 2017, pp. 5692-5705.
IEEE DOI 1710
Haar transforms, discriminative feature generation, object localization, online data-driven sampling, rich local structural information, structural regularization, BibRef


Liu, C.H.[Chang-Hong], Yao, X.[Xuwen], Zhu, Z.H.[Zhi-Hong], Peng, S.H.[Shao-Hu], Zheng, W.P.[Wei-Ping],
A robust tracking method based on the correlation filter and correcting strategy,
ICIVC17(698-702)
IEEE DOI 1708
Binary codes, Collaboration, Computational modeling, Detectors, Monitoring, Probability, Robustness, KCF, TLD, correcting capability, visual, tracking BibRef

Delforouzi, A., Tabatabaei, S.A.H., Shirahama, K., Grzegorzek, M.,
Unknown object tracking in 360-degree camera images,
ICPR16(1798-1803)
IEEE DOI 1705
Cameras, Detectors, Image resolution, Object tracking, Robot vision systems, Shape BibRef

Pal, S.K.,
Plenary speaker: Granular video tracking: Role of r-granules,
IVPR17(1-2)
IEEE DOI 1704
NASA BibRef

Smith, K.[Kaleb], Smith, A.O.[Anthony O.],
Video Tracking with Probabilistic Cooccurrence Feature Extraction,
ISVC16(II: 504-513).
Springer DOI 1701
BibRef

Li, Y., Liu, G.,
Learning a scale-and-rotation correlation filter for robust visual tracking,
ICIP16(454-458)
IEEE DOI 1610
Correlation BibRef

Stühmer, J., Nowozin, S.[Sebastian], Fitzgibbon, A., Szeliski, R., Perry, T., Acharya, S., Cremers, D., Shotton, J.,
Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations,
ICCV15(3577-3585)
IEEE DOI 1602
Cameras BibRef

Ma, C., Huang, J.B., Yang, X., Yang, M.H.,
Hierarchical Convolutional Features for Visual Tracking,
ICCV15(3074-3082)
IEEE DOI 1602
Correlation BibRef

Tang, M., Feng, J.,
Multi-kernel Correlation Filter for Visual Tracking,
ICCV15(3038-3046)
IEEE DOI 1602
Correlation BibRef

Montero, A.S., Lang, J., Laganiere, R.,
Scalable Kernel Correlation Filter with Sparse Feature Integration,
VOT15(587-594)
IEEE DOI 1602
Computational modeling BibRef

Possegger, H.[Horst], Mauthner, T.[Thomas], Bischof, H.[Horst],
In defense of color-based model-free tracking,
CVPR15(2113-2120)
IEEE DOI 1510
BibRef

Dai, M.[Manna], Lin, P.[Peijie], Wu, L.J.[Li-Jun], Chen, Z.C.[Zhi-Cong], Lai, S.L.[Song-Lin], Zhang, J.[Jie], Cheng, S.Y.[Shu-Ying], He, X.J.[Xiang-Jian],
Orderless and Blurred Visual Tracking via Spatio-temporal Context,
MMMod15(I: 25-36).
Springer DOI 1501
BibRef

Gao, Y.C.[Yi-Cheng], Yang, J.[Jian], Wang, H.[Huan], Bai, H.Y.[Hong-Yang],
Object Tracking via Multi-task Gaussian-Laplacian Regression,
ACPR13(405-409)
IEEE DOI 1408
Gaussian noise BibRef

Sugaya, Y.[Yasuyuki], Matsushita, Y.[Yuichi], Kanatani, K.[Kenichi],
Removing Mistracking of Multibody Motion Video Database Hopkins155,
BMVC13(xx-yy).
DOI Link 1402
Results:
WWW Link. Point features for multibody motion. BibRef

Tron, R.[Roberto], Vidal, R.[Rene],
A Benchmark for the Comparison of 3-D Motion Segmentation Algorithms,
CVPR07(1-8).
IEEE DOI
PDF File. 0706
See also Hopkins 155. BibRef

Wang, W.J.[Wei-Jun], Nevatia, R.[Ramakant],
Robust Object Tracking Using Constellation Model with Superpixel,
ACCV12(III:191-204).
Springer DOI 1304
BibRef

Qin, T.[Tao], Zhong, B.[Bineng], Chin, T.J.[Tat-Jun], Wang, H.Z.[Han-Zi],
Matting-driven online learning of Hough forests for object tracking,
ICPR12(2488-2491).
WWW Link. 1302
BibRef

Chu, D.M., Smeulders, A.W.M.,
Thirteen Hard Cases in Visual Tracking,
AVSS10(103-110).
IEEE DOI 1009
BibRef

Qi, F.[Fei], Song, X.W.[Xiao-Wei], Shi, G.M.[Guang-Ming],
LDA based color information fusion for visual objects tracking,
ICIP09(2201-2204).
IEEE DOI 0911
BibRef

Shi, B.[Bo], Cao, Z.L.[Zuo-Liang], Juha, R.N.[Ro-Ning],
Target Recognition and Tracking in Outdoor Environment,
CISP09(1-5).
IEEE DOI 0910
BibRef

Gu, Y.[Yang],
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Long Sequence Matching and Motion .


Last update:Nov 11, 2017 at 13:31:57