16.6.1 Long Sequence Matching and Motion

Chapter Contents (Back)
Motion, Tracking. Tracking. Sequences. Long Sequence. Motion, Many Frames. Matching, Sequence.
See also Point Matching.
See also Long Sequences, Motion Matching.

Chang, E.S.H.[Edward S.H.], Kurz, L.[Ludwik],
Trajectory Detection and Experimental Designs,
CVGIP(27), No. 3, September 1984, pp. 346-368.
Elsevier DOI BibRef 8409

Chang, E.S.H.[Edward S.H.], Kurz, L.[Ludwik],
Object Detection and Experimental Designs,
CVGIP(40), No. 2, November 1987, pp. 147-168.
Elsevier DOI BibRef 8711

Iu, S.L.[Siu-Leong], Wohn, K.Y.[Kwang-Yoen],
Recovery of 3D Motion of a Single Particle,
PR(24), No. 3, 1991, pp. 241-252.
Elsevier DOI BibRef 9100
Earlier:
Estimation of General Rigid Body Motion from a Long Sequence of Images,
ICPR90(I: 217-219).
IEEE DOI BibRef
And:
FLAT MMF: A New Recursive Technique for the 3-D Motion Analysis,
DARPA90(405-417). Claims that constant motion (parameters?) is not needed? Tracking points with a model based on some of the past points, not all. BibRef

Rangarajan, K.[Krishnan], Shah, M.[Mubarak],
Establishing Motion Correspondence,
CVGIP(54), No. 1, July 1991, pp. 56-73.
Elsevier DOI BibRef 9107
And: CVPR91(103-108).
IEEE DOI Propose a proximal uniformity constraint (smooth paths, short distances) for the matching problem (of points -- no features). Gradient-based optical flow is used for the first two frames. BibRef

Rangarajan, K.[Krishnan], Shah, M.[Mubarak],
Interpretation of Motion Trajectories Using Focus of Expansion,
PAMI(14), No. 12, December 1992, pp. 1205-1210.
IEEE DOI Analysis of the locus of the FOE leads to determination of the trajectory. BibRef 9212

Rangarajan, K.[Krishnan], Allen, W.[William], Shah, M.[Mubarak],
Matching Motion Trajectories Using Scale-Space,
PR(26), No. 4, April 1993, pp. 595-610.
Elsevier DOI BibRef 9304
Earlier:
Recognition Using Motion and Shape,
ICPR92(I:255-258).
IEEE DOI BibRef

Shah, M., Rangarajan, K., and Tsai, P.S.,
Motion Trajectories,
SMC(23), 1993, pp. 1138-1150. BibRef 9300
Earlier: CVPR92(839-841).
IEEE DOI BibRef
And:
Generation and Segmentation of Motion Trajectories,
ICPR92(I:74-77).
IEEE DOI BibRef

Blostein, S.D., and Huang, T.S.,
Detecting Small, Moving Objects in Image Sequences Using Sequential Hypothesis Testing,
TSP(39), No. 7, 1991, pp. 1611-1629. BibRef 9100

Kalivas, D.S.[Dimitrios S.], Sawchuk, A.A.[Alexander A.],
A Region Matching Motion Estimation Algorithm,
CVGIP(54), No. 2, September 1991, pp. 275-288.
Elsevier DOI BibRef 9109
Earlier:
A 2-D motion estimation algorithm,
ICPR90(I: 271-273).
IEEE DOI 9006
Basic 2-D motion estimation with region tracking. BibRef

Bober, M.[Miroslaw], Kittler, J.V.[Josef V.],
Estimation of Complex Multimodal Motion: An Approach Based on Robust Statistics and Hough Transform,
IVC(12), No. 10, December 1994, pp. 661-668.
Elsevier DOI BibRef 9412
Earlier: BMVC93(239-248).
PDF File. Hough, Motion. Affine Model. BibRef

Bober, M.[Miroslaw], Kittler, J.V.[Josef V.],
On Combining the Hough Transform and Multiresolution MRFs for Robust Analysis of Complex Motion,
ACCV95(301-305). BibRef 9500
And:
Robust Motion Analysis,
CVPR94(947-952).
IEEE DOI Hough based technique. Comparison of results of different techniques for optical flow. BibRef

Thirumalai, S., Ahuja, N.,
Parallel Distributed Detection of Feature Trajectories in Multiple Discontinuous Motion Image Sequences,
TNN(7), No. 3, May 1996, pp. 594-603. 9606
BibRef
Earlier:
Detection and Segmentation of Feature Trajectories in Multiple, Discontinuous Motion Image Sequences,
DARPA93(621-628). Generate groups of similar motions (not 3-D motions). BibRef

Szeliski, R.S., and Kang, S.B.,
Recovering 3D Shape and Motion from Image Streams Using Non-Linear Least Squares,
JVCIR(5), No. 1, March 1994, pp. 10-28. BibRef 9403
Earlier: CVPR93(752-753).
IEEE DOI BibRef
And: DEC-CRL-93-3, March 1993. A very long sequence (96 frames). BibRef

Fletcher, M.J., Warwick, K., and Mitchell, R.J.,
The Application of a Hybrid Tracking Algorithm to Motion Analysis,
CVPR91(84-89).
IEEE DOI Point tracking for simple motions. BibRef 9100

Fletcher, M.J., and Mitchell, R.J.,
Predicting Multiple Feature Locations for a Class of Dynamic Image Sequences,
IVC(8), No. 3, August 1990, pp. 193-198.
Elsevier DOI BibRef 9008

Costabile, M.F., Guerra, C., and Pieroni, G.G.,
Matching Shapes: A Case Study in Time-Varying Images,
CVGIP(29), No. 3, 1985, pp. 296-310.
Elsevier DOI BibRef 8500
Earlier: A3, A1, A2:
Decomposition of Shape Boundaries in a Problem of Map Sequence Analysis,
ICPR80(618-623). Find the convex pieces of the shape, and apply a tree search on the possible matches of each individual piece (single to multiple match is allowed). BibRef

Pieroni, G.G., Costabile, M.F.,
A Method for Detecting Correspondences in a Sequence of Modifying Shapes,
PRL(3), 1985, pp. 403-412. Snakes. BibRef 8500
Earlier:
Finding Correspondences in Time-Varying Shape Boundaries,
ICPR84(1171-1174). BibRef
Earlier:
Experiments in Dynamic Segmentation,
PRIP79(300-307). BibRef

Costabile, M.F., Pieroni, G.G.,
Detecting Shape Correspondences by Using the Generalized Hough Transform,
ICPR86(589-591). BibRef 8600

Pieroni, G.G.,
A Method for Analyzing Dynamic Processes Represented by Sequences of Maps,
CGIP(10), No. 4, August 1979, pp. 375-387.
Elsevier DOI BibRef 7908

Pieroni, G.G., Freeman, H.,
On the Analysis of Dynamic Map Data,
ICPR78(731-734). BibRef 7800

Tan, T.N., Baker, K.D., Sullivan, G.D.,
3D Structure and Motion Estimation from 2D Image Sequences,
IVC(11), No. 4, May 1993, pp. 203-210.
Elsevier DOI BibRef 9305
Earlier: BMVC92(xx-yy).
PDF File. 9209
BibRef
Earlier: A1, A3, A2:
Structure from Constrained Motion Using Point Correspondences,
BMVC91(xx-yy).
PDF File. 9109

See also Recognizing Objects on the Ground-Plane. BibRef

Tan, T.N., Sullivan, G.D., Baker, K.D.,
Linear Algorithms for Multi-Frame Structure from Constrained Motion,
BMVC94(xx-yy).
PDF File. 9409
BibRef

Zakhor, A., Lari, F.,
Edge-Based 3-D Camera Motion Estimation with Application to Video Coding,
IP(2), No. 4, October 1993, pp. 481-498.
IEEE DOI BibRef 9310

Lee, C.H.[Chia-Hoang], Joshi, A.[Anupam],
Correspondence Problem in Image Sequence Analysis,
PR(26), No. 1, January 1993, pp. 47-61.
Elsevier DOI Match using geometric constraints BibRef 9301

Rudd, J.G., Marsh, R.A., and Roecker, J.A.,
Surveillance and tracking of ballistic missile launches,
IBMRD(38), No. 2, February 1994, pp. 195-216. BibRef 9402

Vieville, T., Faugeras, O.D., Luong, Q.T.,
Motion Of Points And Lines In The Uncalibrated Case,
IJCV(17), No. 1, January 1996, pp. 7-41.
Springer DOI BibRef 9601

Vieville, T., Luong, Q.T.,
Computing Motion and Structure in Image Sequences without Calibration,
ICPR94(A:420-425).
IEEE DOI BibRef 9400

Vieville, T.[Thierry], Zeller, C.[Cyril], and Robert, L.[Luc],
Using Collineations to Compute Motion and Structure in an Uncalibrated Image Sequence,
IJCV(20), No. 3, 1996, pp. 213-242. BibRef 9600
Earlier:
Recovering Motion and Structure from a Set of Planar Patches in an Uncalibrated Image Sequence,
ICPR94(A:637-640).
IEEE DOI BibRef

Huang, C.L.[Chung-Lin], Wu, C.H.[Chi-Hou],
Dynamic Scene Analysis Using Path and Shape Coherence,
PR(25), No. 5, May 1992, pp. 445-461.
Elsevier DOI BibRef 9205

Griffin, P.M., Messimer, S.L.,
Feature Point Tracking in Time-Varying Images,
PRL(11), 1990, pp. 843-848. BibRef 9000

Rosenberg, Y.[Yoav], Werman, M.[Michael],
Representing Local Motion as a Probability Distribution Matrix and Object Tracking,
DARPA97(153-158). BibRef 9700

Åström, K.[Kalle], Kahl, F.[Fredrik],
Motion Estimation in Image Sequences Using the Deformation of Apparent Contours,
PAMI(21), No. 2, February 1999, pp. 114-127.
IEEE DOI BibRef 9902
Earlier: A2, A1: ICCV98(939-942).
IEEE DOI BibRef
And: SSAB97(Computer Vision). 9703
Camera motion using unknown surfaces. Uses epipolar constraints. BibRef

Wagner, R.[Robert], Liu, F.Y.[Fei-Yu], Donner, K.[Klaus],
Robust Motion Estimation for Calibrated Cameras from Monocular Image Sequences,
CVIU(73), No. 2, February 1999, pp. 258-268.
DOI Link BibRef 9902

Gibson, D., Spann, M.,
Robust Motion Trajectory Estimation for Long Image Sequences with Applications to Motion Compensated Prediction,
PRAI(13), No. 5, August 1999, pp. 781. 0005
BibRef

Zhang, T.[Tong], Tomasi, C.[Carlo],
On the Consistency of Instantaneous Rigid Motion Estimation,
IJCV(46), No. 1, January 2002, pp. 51-79.
DOI Link 0201
BibRef
Earlier:
Fast, Robust, and Consistent Camera Motion Estimation,
CVPR99(I: 164-170).
IEEE DOI Using robust techniques to improve estimate as number of points increases. BibRef

Cadman, L., Tjahjadi, T.,
Efficient Three-Dimensional Metric Object Modeling From Uncalibrated Image Sequences,
SMC-B(34), No. 2, April 2004, pp. 856-876.
IEEE Abstract. 0404
BibRef
Earlier:
Simultaneous Feature Tracking and Three-dimensional Object Reconstruction from an Image Sequence,
ICIP01(II: 391-394).
IEEE DOI 0108
BibRef

Arnaud, E.[Elise], Mémin, E.[Etienne], Cernuschi-Frias, B.,
Conditional Filters for Image Sequence-Based Tracking: Application to Point Tracking,
IP(14), No. 1, January 2005, pp. 63-79.
IEEE DOI 0501
BibRef

Arnaud, E.[Elise], Mémin, E.[Etienne],
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods,
IJCV(80), No. 1, October 2008, pp. xx-yy.
Springer DOI 0809
BibRef
And: IJCV(74), No. 1, August 2007, pp. 75-102.
Springer DOI 0705
BibRef
Earlier:
Optimal Importance Sampling for Tracking in Image Sequences: Application to Point Tracking,
ECCV04(Vol III: 302-314).
Springer DOI 0405
Sequential Monte Carlo methods (also called particle filters) BibRef

Shih, M.Y.[Ming-Yu], Tseng, D.C.[Din-Chang],
A wavelet-based multiresolution edge detection and tracking,
IVC(23), No. 4, 1 April 2005, pp. 441-451.
Elsevier DOI 0501
BibRef

Zhu, G.P.[Guo-Pu], Zeng, Q.S.[Qing-Shuang], Wang, C.H.[Chang-Hong],
Efficient edge-based object tracking,
PR(39), No. 11, November 2006, pp. 2223-2226.
Elsevier DOI 0608
Keywords: Image edge; Motion estimation; Object tracking BibRef

Cossalter, M., Valenzise, G., Tagliasacchi, M., Tubaro, S.,
Joint Compressive Video Coding and Analysis,
MultMed(12), No. 3, March 2010, pp. 168-183.
IEEE DOI 1003
BibRef

Cossalter, M., Tagliasacchi, M., Valenzise, G.,
Privacy-Enabled Object Tracking in Video Sequences Using Compressive Sensing,
AVSBS09(436-441).
IEEE DOI 0909
BibRef

Chen, M.J.[Min-Jie], Xu, M.T.[Man-Tao], Franti, P.[Pasi],
A Fast O(N) Multiresolution Polygonal Approximation Algorithm for GPS Trajectory Simplification,
IP(21), No. 5, May 2012, pp. 2770-2785.
IEEE DOI 1204
BibRef

Chen, M.J.[Min-Jie], Xu, M.T.[Man-Tao], Franti, P.[Pasi],
Compression of GPS trajectories using optimized approximation,
ICPR12(3180-3183).
WWW Link. 1302
BibRef

Fishbain, B.[Barak], Hochbaum, D.[Dorit], Yang, Y.[Yan],
A new approach for real-time target tracking in videos,
SPIE(Newsroom), January 29, 2013.
DOI Link 1305
A generic, graph-theory-based tracking method in videos helps solve the problem of tracking. BibRef

Zhang, C.L.[Can-Long], Jing, Z.L.[Zhong-Liang], Tang, Y.P.[Yan-Ping], Jin, B.[Bo], Xiao, G.[Gang],
Locally discriminative stable model for visual tracking with clustering and principle component analysis,
IET-CV(7), No. 3, 2013, pp. 151-162.
DOI Link 1307
BibRef

Muckell, J.[Jonathan], Olsen, Jr., P.W.[Paul W.], Hwang, J.H.[Jeong-Hyon], Lawson, C.T.[Catherine T.], Ravi, S.S.,
Compression of Trajectory Data: A Comprehensive Evaluation and New Approach,
GeoInfo(18), No. 3, July 2014, pp. 435-460.
Springer DOI 1407
BibRef

Martínez, C.[Carol], Campoy, P.[Pascual], Mondragón, I.F.[Iván F.], Sánchez-Lopez, J.L.[José Luis], Olivares-Méndez, M.A.[Miguel A.],
HMPMR strategy for real-time tracking in aerial images, using direct methods,
MVA(25), No. 5, July 2014, pp. 1283-1308.
Springer DOI 1407
HMPMR: Hierarchical Multi-Parametric and Multi-Resolution. BibRef

Zhang, K.H.[Kai-Hua], Zhang, L.[Lei], Yang, M.H.[Ming-Hsuan],
Fast Compressive Tracking,
PAMI(36), No. 10, October 2014, pp. 2002-2015.
IEEE DOI 1410
BibRef
Earlier:
Real-Time Compressive Tracking,
ECCV12(III: 864-877).
Springer DOI 1210
Bayes methods
See also Fast Visual Tracking via Dense Spatio-temporal Context Learning.
See also Real-Time Object Tracking Via Online Discriminative Feature Selection. BibRef

Huang, H.T.[Hong-Tu], Bi, D.Y.[Du-Yan], Zha, Y.F.[Yu-Fei], Ma, S.P.[Shi-Ping], Gao, S.[Shan], Liu, C.[Chang],
Robust visual tracking based on product sparse coding,
PRL(56), No. 1, 2015, pp. 52-59.
Elsevier DOI 1503
Visual tracking BibRef

Chavoshi, S.H.[Seyed Hossein], de Baets, B.[Bernard], Neutens, T.[Tijs], Delafontaine, M.[Matthias], de Tré, G.[Guy], van de Weghe, N.[Nico],
Movement Pattern Analysis Based on Sequence Signatures,
IJGI(4), No. 3, 2015, pp. 1605.
DOI Link 1511
BibRef

Lebeda, K., Hadfield, S., Matas, J.G., Bowden, R.,
Texture-Independent Long-Term Tracking Using Virtual Corners,
IP(25), No. 1, January 2016, pp. 359-371.
IEEE DOI 1601
BibRef
Earlier:
Long-Term Tracking through Failure Cases,
VOT13(153-160)
IEEE DOI 1403
Apertures. edge detection BibRef

Lebeda, K.[Karel], Hadfield, S.[Simon], Bowden, R.[Richard],
Exploring Causal Relationships in Visual Object Tracking,
ICCV15(3065-3073)
IEEE DOI 1602
Cameras; Entropy; Kernel; Object tracking; Visualization BibRef

Miao, Q.[Quan], Zhang, C.[Chun], Meng, L.[Long],
Feature-Based On-Line Object Tracking Combining Both Keypoints and Quasi-Keypoints Matching,
IEICE(E99-D), No. 4, April 2016, pp. 1264-1267.
WWW Link. 1604
BibRef

Henderson, C.[Craig], Izquierdo, E.[Ebroul],
Robust Feature Matching in Long-Running Poor-Quality Videos,
CirSysVideo(26), No. 6, June 2016, pp. 1161-1174.
IEEE DOI 1606
Cameras. Match key point and region features. BibRef

Miao, Q.[Quan], Shi, C.[Chenbo], Meng, L.[Long], Cheng, G.[Guang],
On-Line Rigid Object Tracking via Discriminative Feature Classification,
IEICE(E99-D), No. 11, November 2016, pp. 2824-2827.
WWW Link. 1611
BibRef

Wang, R.[Rui], Dong, H.[Hao], Han, T.X.[Tony X.], Mei, L.[Lei],
Robust tracking via monocular active vision for an intelligent teaching system,
VC(32), No. 11, November 2016, pp. 1379-1394.
WWW Link. 1611
BibRef

Zhao, L.J.[Liu-Jun], Zhao, Q.J.[Qing-Jie], Liu, H.[Hao], Lv, P.[Peng], Gu, D.B.[Dong-Bing],
Structural sparse representation-based semi-supervised learning and edge detection proposal for visual tracking,
VC(33), No. 9, September 2017, pp. 1169-1184.
WWW Link. 1708
BibRef

Wang, M.M.[Min-Min], Sun, S.L.[Sheng-Li], Li, Y.J.[Ye-Jin],
A Compressive Tracking Method Based on Gaussian Differential Graph and Weighted Cosine Similarity Metric,
SPLetters(25), No. 4, April 2018, pp. 501-505.
IEEE DOI 1804
Bayes methods, compressed sensing, feature extraction, graph theory, object tracking, signal classification, visual tracking BibRef

Wang, N.[Ning], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang],
Reliable Re-Detection for Long-Term Tracking,
CirSysVideo(29), No. 3, March 2019, pp. 730-743.
IEEE DOI 1903
Target tracking, Reliability, Correlation, Detectors, Feature extraction, Task analysis, Long-term tracking, feature combination BibRef

Wang, N.[Ning], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang],
Learning Diverse Models for End-to-End Ensemble Tracking,
IP(30), 2021, pp. 2220-2231.
IEEE DOI 2102
feature extraction, image fusion, image representation, learning (artificial intelligence), object tracking, diverse models BibRef

Wang, N.[Ning], Zhou, W.G.[Wen-Gang], Wang, J.[Jie], Li, H.Q.[Hou-Qiang],
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking,
CVPR21(1571-1580)
IEEE DOI 2111
Bridges, Visualization, Target tracking, Pipelines, Transformers, Search problems BibRef

Wang, N.[Ning], Zhou, W.G.[Wen-Gang], Tian, Q.[Qi], Li, H.Q.[Hou-Qiang],
Cascaded Regression Tracking: Towards Online Hard Distractor Discrimination,
CirSysVideo(31), No. 4, April 2021, pp. 1580-1592.
IEEE DOI 2104
Target tracking, Visualization, Robustness, Adaptation models, Benchmark testing, Training, Real-time systems, Visual tracking, hard distractor BibRef

Zheng, X.X.[Xiao-Xu], Ramesh, B.[Bharath], Gao, Z.[Zhi], Yang, Y.[Yue], Xiang, C.[Cheng],
A novel framework for robust long-term object tracking in real-time,
MVA(30), No. 3, April 2019, pp. 529-539.
Springer DOI 1906
BibRef

Ramesh, B.[Bharath], Zhang, S.H.[Shi-Hao], Yang, H.[Hong], Ussa, A.[Andres], Ong, M.[Matthew], Orchard, G.[Garrick], Xiang, C.[Cheng],
e-TLD: Event-Based Framework for Dynamic Object Tracking,
CirSysVideo(31), No. 10, October 2021, pp. 3996-4006.
IEEE DOI 2110
Cameras, Object tracking, Target tracking, Detectors, Shape, Robot vision systems, Training, Event-based vision, dynamic motion BibRef

Dai, W.C.[Wei-Cong], Jin, L.X.[Long-Xu], Li, G.N.[Guo-Ning],
Long-term adaptive tracking via complementary trackers,
IET-IPR(13), No. 9, 18 July 2019, pp. 1569-1577.
DOI Link 1907
BibRef

Gao, J.Y.[Jun-Yu], Zhang, T.Z.[Tian-Zhu], Xu, C.S.[Chang-Sheng],
SMART: Joint Sampling and Regression for Visual Tracking,
IP(28), No. 8, August 2019, pp. 3923-3935.
IEEE DOI 1907
feedforward neural nets, image sampling, learning (artificial intelligence), object tracking, sampling and regression BibRef

Bouthemy, P.[Patrick], Toledo Acosta, B.M.[Bertha Mayela], Delyon, B.[Bernard],
Robust Model Selection in 2D Parametric Motion Estimation,
JMIV(61), No. 7, September 2019, pp. 1022-1036.
Springer DOI 1908
BibRef
Earlier:
Robust selection of parametric motion models in image sequences,
ICIP16(3743-3747)
IEEE DOI 1610
Complexity theory BibRef

Li, T.[Tao], Zhao, S.Y.[San-Yuan], Meng, Q.H.[Qing-Hao], Chen, Y.F.[Yu-Feng], Shen, J.B.[Jian-Bing],
A stable long-term object tracking method with re-detection strategy,
PRL(127), 2019, pp. 119-127.
Elsevier DOI 1911
Correlation filter, Long-term tracking, Re-detection BibRef

Liao, J.W.[Jia-Wen], Qi, C.[Chun], Cao, J.Z.[Jian-Zhong], Ren, L.[Long], Zhang, G.P.[Gao-Peng],
Real-time long-term tracker with tracking-verification-detection-refinement,
JVCIR(72), 2020, pp. 102896.
Elsevier DOI 2010
Correlation filter, Occlusion, Long-term, Detector, Real-time BibRef

Zhao, S.H.[Shaoc-Huan], Xu, T.Y.[Tian-Yang], Wu, X.J.[Xiao-Jun], Zhu, X.F.[Xue-Feng],
Adaptive feature fusion for visual object tracking,
PR(111), 2021, pp. 107679.
Elsevier DOI 2012
Visual tracking, Deep neural network, Feature fusion, Online adaptation BibRef

Chen, L.[Lulu], Zhao, Y.Q.[Yong-Qiang], Yao, J.X.[Jia-Xin], Chen, J.X.[Jia-Xin], Li, N.[Ning], Chan, J.C.W.[Jonathan Cheung-Wai], Kong, S.G.[Seong G.],
Object Tracking in Hyperspectral-Oriented Video with Fast Spatial-Spectral Features,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Tu, Z.Y.[Zhi-Yong], Lou, Y.D.[Yi-Dong], Guo, W.F.[Wen-Fei], Song, W.W.[Wei-Wei], Wang, Y.S.[Yu-Sheng],
Design and Validation of a Cascading Vector Tracking Loop in High Dynamic Environments,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Yu, L.[Lang], Zhang, H.L.[Huan-Long], Yu, J.Y.[Jun-Yang], Qiao, B.J.[Bao-Jun],
Online-adaptive classification and regression network with sample-efficient meta learning for long-term tracking,
IVC(112), 2021, pp. 104181.
Elsevier DOI 2107
Long-term tracking, Target regression, Online learning, Meta learning BibRef

Zhang, Y.H.[Yun-Hua], Wang, L.J.[Li-Jun], Wang, D.[Dong], Qi, J.Q.[Jin-Qing], Lu, H.C.[Hu-Chuan],
Learning Regression and Verification Networks for Robust Long-term Tracking,
IJCV(129), No. 9, September 2021, pp. 2536-2547.
Springer DOI 2108
BibRef

Chen, X.[Xin], Kang, B.[Ben], Wang, D.[Dong], Li, D.D.[Dong-Dong], Lu, H.C.[Hu-Chuan],
Efficient Visual Tracking via Hierarchical Cross-attention Transformer,
VOT22(461-477).
Springer DOI 2304
BibRef

Lukezic, A.[Alan], Zajc, L.C.[Luka Cehovin], Vojír, T.[Tomáš], Matas, J.G.[Jirí G.], Kristan, M.[Matej],
Performance Evaluation Methodology for Long-Term Single-Object Tracking,
Cyber(51), No. 12, December 2021, pp. 6305-6318.
IEEE DOI 2112
Target tracking, Benchmark testing, Performance evaluation, Visualization, Annotations, Current measurement, visual object tracking BibRef

Lukežic, A.[Alan], Matas, J.G.[Jirí G.], Kristan, M.[Matej],
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking,
PAMI(44), No. 12, December 2022, pp. 9742-9755.
IEEE DOI 2212
Target tracking, Feature extraction, Object segmentation, Location awareness, Adaptation models, Estimation, Visualization, single-shot segmentation BibRef

Li, Z.Y.[Zhi-Yong], Nai, K.[Ke], Li, G.J.[Gui-Ji], Jiang, S.L.[Shi-Long],
Learning a Dynamic Feature Fusion Tracker for Object Tracking,
ITS(23), No. 2, February 2022, pp. 1479-1491.
IEEE DOI 2202
Target tracking, Correlation, Color, Visualization, Object tracking, Fuses, Robustness, Visual tracking, correlation filters, re-detection operation BibRef

Nai, K.[Ke], Li, Z.Y.[Zhi-Yong], Wang, H.D.[Hai-Dong],
Dynamic feature fusion with spatial-temporal context for robust object tracking,
PR(130), 2022, pp. 108775.
Elsevier DOI 2206
Object tracking, Dynamic feature fusion, Spatial-temporal context, Correlation filters framework BibRef

Yu, L.[Lang], Qiao, B.J.[Bao-Jun], Zhang, H.L.[Huan-Long], Yu, J.Y.[Jun-Yang], He, X.[Xin],
LTST: Long-term segmentation tracker with memory attention network,
IVC(119), 2022, pp. 104374.
Elsevier DOI 2202
Long-term tracking, Object segmentation, Memory network, Attention mechanism BibRef

Qin, H.[Huai], Yu, C.Q.[Chang-Qian], Gao, C.X.[Chang-Xin], Sang, N.[Nong],
D2T: A Framework For transferring detection to tracking,
PR(126), 2022, pp. 108544.
Elsevier DOI 2204
Object tracking, Object detection, Transferring detection to tracking BibRef

Li, G.C.[Gu-Chong], Li, G.[Gang], He, Y.[You],
Distributed GGIW-CPHD-Based Extended Target Tracking Over a Sensor Network,
SPLetters(29), 2022, pp. 842-846.
IEEE DOI 2204
Target tracking, Computational modeling, Symmetric matrices, Weight measurement, Standards, Radio frequency, Gamma distribution, multi-agent system BibRef

Dunnhofer, M.[Matteo], Simonato, K.[Kristian], Micheloni, C.[Christian],
Combining complementary trackers for enhanced long-term visual object tracking,
IVC(122), 2022, pp. 104448.
Elsevier DOI 2205
Video tracking, Visual object tracking, Long-term visual tracking, Deep learning BibRef

Dunnhofer, M.[Matteo], Micheloni, C.[Christian],
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking,
ICPR22(5132-5139)
IEEE DOI 2212
Location awareness, Deep learning, Visualization, Target tracking, Benchmark testing, Pattern recognition, Behavioral sciences BibRef

Yang, L.[Lei], Zhang, W.P.[Wen-Peng], Jiang, W.D.[Wei-Dong],
Recognition of Ballistic Targets by Fusing Micro-Motion Features with Networks,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zhao, H.J.[Hao-Jie], Yan, B.[Bin], Wang, D.[Dong], Qian, X.S.[Xue-Sheng], Yang, X.Y.[Xiao-Yun], Lu, H.C.[Hu-Chuan],
Effective Local and Global Search for Fast Long-Term Tracking,
PAMI(45), No. 1, January 2023, pp. 460-474.
IEEE DOI 2212
Target tracking, Search problems, Task analysis, Proposals, Object tracking, Correlation, Benchmark testing, global re-detection BibRef

Xu, X.[Xiang], Zhao, J.[Jian], Wu, J.M.[Jian-Min], Shen, F.[Furao],
Switch and Refine: A Long-Term Tracking and Segmentation Framework,
CirSysVideo(33), No. 3, March 2023, pp. 1291-1304.
IEEE DOI 2303
Target tracking, Task analysis, Switches, Object tracking, Learning systems, Estimation, Object segmentation, visual object segmentation BibRef

Qian, K.[Kun], Chen, P.[Peng], Zhao, D.[Dong],
GOMT: Multispectral video tracking based on genetic optimization and multi-features integration,
IET-IPR(17), No. 5, 2023, pp. 1578-1589.
DOI Link 2304
computer vision, correlation methods, fast Fourier transforms, feature extraction, feature selection, image classification, image fusion BibRef

Ma, J.[Jie], Lan, X.Y.[Xiang-Yuan], Zhong, B.N.[Bi-Neng], Li, G.R.[Guo-Rong], Tang, Z.J.[Zhen-Jun], Li, X.X.[Xian-Xian], Ji, R.R.[Rong-Rong],
Robust Tracking via Uncertainty-Aware Semantic Consistency,
CirSysVideo(33), No. 4, April 2023, pp. 1740-1751.
IEEE DOI 2304
Uncertainty, Feature extraction, Target tracking, Semantics, Correlation, Estimation, Adaptation models, Object tracking, uncertainty estimation BibRef

Fu, Y.K.[Ying-Kai], Li, M.[Meng], Liu, W.X.[Wen-Xi], Wang, Y.C.[Yuan-Chen], Zhang, J.Q.[Ji-Qing], Yin, B.C.[Bao-Cai], Wei, X.P.[Xiao-Peng], Yang, X.[Xin],
Distractor-Aware Event-Based Tracking,
IP(32), 2023, pp. 6129-6141.
IEEE DOI 2311
BibRef

Wang, X.[Xiao], Li, J.N.[Jia-Ning], Zhu, L.[Lin], Zhang, Z.P.[Zhi-Peng], Chen, Z.[Zhe], Li, X.[Xin], Wang, Y.W.[Yao-Wei], Tian, Y.H.[Yong-Hong], Wu, F.[Feng],
VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows,
Cyber(54), No. 3, March 2024, pp. 1997-2010.
IEEE DOI Code:
WWW Link. 2402
Cameras, Target tracking, Task analysis, Benchmark testing, Transformers, Object tracking, Feature extraction, visual tracking BibRef

Wang, X.[Xiao], Shu, X.J.[Xiu-Jun], Zhang, Z.P.[Zhi-Peng], Jiang, B.[Bo], Wang, Y.W.[Yao-Wei], Tian, Y.H.[Yong-Hong], Wu, F.[Feng],
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark,
CVPR21(13758-13768)
IEEE DOI 2111
Target tracking, Natural languages, Video sequences, Semantics, Switches, Benchmark testing, Search problems BibRef

Liu, J.[Jun], Luo, Z.Q.[Zhong-Qiang], Xiong, X.Z.[Xing-Zhong],
Online Learning Samples and Adaptive Recovery for Robust RGB-T Tracking,
CirSysVideo(34), No. 2, February 2024, pp. 724-737.
IEEE DOI 2402
Tracking, Target tracking, Detectors, Training, Lighting, Correlation, Cameras, RGB-T tracking, long-term tracking, multimodal fusion, object detection BibRef

Dai, K.[Kuai], Li, X.[Xutao], Ye, Y.M.[Yun-Ming], Wang, Y.[Yaowei], Feng, S.S.[Shan-Shan], Xian, D.[Di],
Exploring and Exploiting High-Order Spatial-Temporal Dynamics for Long-Term Frame Prediction,
CirSysVideo(34), No. 3, March 2024, pp. 1841-1856.
IEEE DOI 2403
Dynamics, Predictive models, Correlation, Training, Task analysis, Satellites, Market research, Long-term, high-order motion patterns BibRef


Doersch, C.[Carl], Yang, Y.[Yi], Vecerik, M.[Mel], Gokay, D.[Dilara], Gupta, A.[Ankush], Aytar, Y.[Yusuf], Carreira, J.[Joao], Zisserman, A.[Andrew],
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement,
ICCV23(10027-10038)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zheng, Y.[Yang], Harley, A.W.[Adam W.], Shen, B.[Bokui], Wetzstein, G.[Gordon], Guibas, L.J.[Leonidas J.],
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking,
ICCV23(19798-19808)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cetintas, O.[Orcun], Brasó, G.[Guillem], Leal-Taixé, L.[Laura],
Unifying Short and Long-Term Tracking with Graph Hierarchies,
CVPR23(22877-22887)
IEEE DOI 2309
BibRef

Wang, J.[Jianren], Wang, X.[Xin], Shang-Guan, Y.[Yue], Gupta, A.[Abhinav],
Wanderlust: Online Continual Object Detection in the Real World,
ICCV21(10809-10818)
IEEE DOI 2203
Measurement, Annotations, Object detection, Machine learning, Detectors, Benchmark testing, Datasets and evaluation, Detection and localization in 2D and 3D BibRef

Yu, B.[Bin], Tang, M.[Ming], Zheng, L.[Linyu], Zhu, G.[Guibo], Wang, J.Q.[Jin-Qiao], Feng, H.[Hao], Feng, X.T.[Xue-Tao], Lu, H.Q.[Han-Qing],
High-Performance Discriminative Tracking with Transformers,
ICCV21(9836-9845)
IEEE DOI 2203
Visualization, Target tracking, Pipelines, Benchmark testing, Transformers, Motion and tracking, BibRef

Jiang, S.H.[Shi-Hao], Campbell, D.[Dylan], Lu, Y.[Yao], Li, H.D.[Hong-Dong], Hartley, R.I.[Richard I.],
Learning to Estimate Hidden Motions with Global Motion Aggregation,
ICCV21(9752-9761)
IEEE DOI 2203
Code, Motion.
WWW Link. Image motion analysis, Codes, Ultraviolet sources, Estimation, Benchmark testing, Transformers, Motion and tracking, Stereo, 3D from multiview and other sensors BibRef

Xu, L.[Liang], Niu, R.X.[Rui-Xin],
Tracking Visual Object As An Extended Target,
ICIP21(664-668)
IEEE DOI 2201
Visualization, Target tracking, Shape, Neural networks, Kinematics, Search problems, Numerical models, Visual Object Tracking, Convolutional Neural Network BibRef

Bian, T.L.[Tian-Ling], Hua, Y.[Yang], Song, T.[Tao], Xue, Z.G.[Zhen-Gui], Ma, R.[Ruhui], Robertson, N.[Neil], Guan, H.B.[Hai-Bing],
VTT: Long-term Visual Tracking with Transformers,
ICPR21(9585-9592)
IEEE DOI 2105
Visualization, Target tracking, Aggregates, Benchmark testing, Proposals, Labeling BibRef

Li, Z., Wang, Q., Gao, J., Li, B., Hu, W.,
Globally Spatial-Temporal Perception: a Long-Term Tracking System,
ICIP20(2066-2070)
IEEE DOI 2011
Target tracking, Feature extraction, Head, Trajectory, Object tracking, Robustness, Visual object tracking, motion model BibRef

Yin, T.W.[Tian-Wei], Zhou, X.Y.[Xing-Yi], Krähenbühl, P.[Philipp],
Center-based 3D Object Detection and Tracking,
CVPR21(11779-11788)
IEEE DOI 2111
Solid modeling, Computational modeling, MIMICs, Fitting, Detectors BibRef

Zhou, X.Y.[Xing-Yi], Koltun, V.[Vladlen], Krähenbühl, P.[Philipp],
Tracking Objects as Points,
ECCV20(IV:474-490).
Springer DOI 2011
BibRef

Dai, K., Zhang, Y., Wang, D., Li, J., Lu, H., Yang, X.,
High-Performance Long-Term Tracking With Meta-Updater,
CVPR20(6297-6306)
IEEE DOI 2008
Target tracking, Visualization, Switches, Reliability, Noise measurement, Benchmark testing, Task analysis BibRef

Du, F., Liu, P., Zhao, W., Tang, X.,
Correlation-Guided Attention for Corner Detection Based Visual Tracking,
CVPR20(6835-6844)
IEEE DOI 2008
Target tracking, Corner detection, Estimation, Correlation, Feature extraction, Visualization, Training BibRef

Karthik, S., Moudgil, A., Gandhi, V.,
Exploring 3 R's of Long-term Tracking: Re-detection, Recovery and Reliability,
WACV20(1000-1009)
IEEE DOI 2006
Target tracking, Reliability, Visualization, Correlation, Clutter BibRef

Yan, B., Zhao, H., Wang, D., Lu, H., Yang, X.,
'Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-Term Tracking,
ICCV19(2385-2393)
IEEE DOI 2004
Code, Tracking.
WWW Link. object tracking, search problems, robust target verifier, tracked object, local search, image-wide global search. BibRef

Wu, H., Yang, X., Yang, Y., Liu, G.,
Flow Guided Short-Term Trackers with Cascade Detection for Long-Term Tracking,
VisDrone19(170-178)
IEEE DOI 2004
image sequences, object detection, object tracking, flow_MDNet_RPN, long-term tracking algorithm, BibRef

Zhang, W., Wang, H., Huang, Z., Li, Y., Zhou, J., Jiao, L.,
Accuracy and Long-Term Tracking via Overlap Maximization Integrated with Motion Continuity,
VisDrone19(109-117)
IEEE DOI 2004
feature extraction, image classification, object detection, object tracking, regression analysis, state estimation, BibRef

Liu, H., Hu, Q., Li, B., Guo, Y.,
Long-term Object Tracking with Instance Specific Proposals,
ICPR18(1628-1633)
IEEE DOI 1812
Proposals, Target tracking, Adaptation models, Generators, Error correction, Computational modeling, Robustness BibRef

Morgacheva, A.I., Kulikov, V.A., Kosykh, V.P.,
Dynamic Keypoint-based Algorithm of Object Tracking,
PTVSBB17(79-82).
DOI Link 1805
BibRef

Dai, K., Wang, Y., Yan, X.,
Long-term object tracking based on siamese network,
ICIP17(3640-3644)
IEEE DOI 1803
Benchmark testing, Convolution, Real-time systems, Robustness, Target tracking, Visual Tracking BibRef

Ramakrishnan, S.K.[Santhosh K.], Ravindran, S.K.[Swarna Kamlam], Mittal, A.[Anurag],
CoMaL Tracking: Tracking Points at the Object Boundaries,
PETS17(2133-2142)
IEEE DOI 1709
Detectors, Feature extraction, Image edge detection, Image segmentation, Robustness, Shape BibRef

Zhang, L., Cai, Y.Q.[Yuan-Qiang], Ullah, Z., Luo, T.,
MLPF algorithm for tracking fast moving target against light interference,
ICPR16(3939-3944)
IEEE DOI 1705
Interference, Mathematical model, Monte Carlo methods, Probability density function, State estimation, Target, tracking BibRef

Baumann, F.[Florian], Dayangac, E.[Enes], Aulinas, J.[Josep], Zobel, M.[Matthias],
MedianStruck for long-term tracking applications,
IPTA16(1-6)
IEEE DOI 1703
computer vision
See also Struck: Structured Output Tracking with Kernels. BibRef

Xu, J.Q.[Jian-Qiang], Lu, Y.[Yao],
Robust Visual Tracking Based on Multi-channel Compressive Features,
MMMod17(I: 341-352).
Springer DOI 1701
BibRef

de Almeida Maia, H., de Oliveira, F.L.M., Bernardes Vieira, M.,
Independent selection and validation for tracking-learning-detection,
ICIP16(3469-3473)
IEEE DOI 1610
Color BibRef

Tan, K.[Kai], Li, W.H.[Wei-Hai],
A novel moving parameter estimation approach of fast moving targets based on phase extraction,
ICIP15(2075-2079)
IEEE DOI 1512
Fast moving targets imaging BibRef

Rampal, K.[Karon], Sakurai, K.[Kazuyuki], Imaoka, H.[Hitoshi],
Occlusion handling in feature point tracking using ranked parts based models,
ICIP15(740-744)
IEEE DOI 1512
Feature Point; Occlusion; Tracking BibRef

Islam, M.A., Rasheduzzaman, M., Lutfe Elahi, M.M., Poon, B., Amin, M.A., Yan, H.,
Feature fusion for robust object tracking,
ICWAPR15(138-145)
IEEE DOI 1511
feature extraction BibRef

Ryt, A.[Artur], Sobel, D.[Dawid], Kwiatkowski, J.[Jan], Domzal, M.[Mariusz], Jedrasiak, K.[Karol], Nawrat, A.[Aleksander],
Real-Time Laser Point Tracking,
ICCVG14(542-551).
Springer DOI 1410
BibRef

Jedrasiak, K.[Karol], Andrzejczak, M.[Mariusz], Nawrat, A.[Aleksander],
SETh: The Method for Long-Term Object Tracking,
ICCVG14(302-315).
Springer DOI 1410
BibRef

Supancic, III, J.S.[James Steven], Ramanan, D.[Deva],
Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning,
ICCV17(322-331)
IEEE DOI 1802
decision making, learning (artificial intelligence), object tracking, video streaming, Internet videos, Videos BibRef

Supancic, III, J.S.[James Steven], Ramanan, D.[Deva],
Self-Paced Learning for Long-Term Tracking,
CVPR13(2379-2386)
IEEE DOI 1309
learning; object tracking; self paced learning; tracking BibRef

Stanco, F.[Filippo], Allegra, D.[Dario], Milotta, F.L.M.[Filippo Luigi Maria],
Detection and Correction of Mistracking in Digitalized Analog Video,
MM4CH13(218-227).
Springer DOI 1309
BibRef

Hou, J.[Jie], Mao, Y.B.[Yao-Bin], Sun, J.S.[Jin-Sheng],
Visual tracking by separability-maximum online boosting,
ICARCV12(1053-1058).
IEEE DOI 1304
BibRef

Shen, D.[Dong], Wang, Y.Q.[You-Qing],
Iterative learning control for stochastic point-to-point tracking system,
ICARCV12(480-485).
IEEE DOI 1304
BibRef

Mukherjee, A.[Arpita], Sengupta, A.[Aparajita], Mukherjee, D.[Debaprasad],
Filter design for tracking of ballistic target missile using seeker measurements with time lag,
ICSIPR13(351-355).
IEEE DOI 1304
BibRef

Rubinstein, M.[Michael], Liu, C.[Ce],
Towards Longer Long-Range Motion Trajectories,
BMVC12(53).
DOI Link 1301
BibRef

Kozera, R.[Ryszard], Smietanka, M.[Mateusz],
Sharpness in Trajectory Estimation by Piecewise-quadratics(-cubics) and Cumulative Chords,
ICCVG12(148-155).
Springer DOI 1210
BibRef

Collins, R.T.[Robert T.],
Multitarget data association with higher-order motion models,
CVPR12(1744-1751).
IEEE DOI 1208
for linking into trajectories BibRef

Kamberov, G.[George], Kamberova, G.[Gerda], Burlick, M.[Matt], Karydas, L.[Lazaros], Luczynski, B.[Bart],
Collaborative Track Analysis, Data Cleansing, and Labeling,
ISVC11(I: 718-727).
Springer DOI 1109
Noise in track (trajectory) data. BibRef

Bassiouny, M.[Mahmoud], El-Saban, M.[Motaz],
Object matching using feature aggregation over a frame sequence,
WACV11(95-102).
IEEE DOI 1101
Match to models (database) over a sequence. Features change over time. BibRef

Tehrani, M.M.[Mehdi Mazaheri], Seresht, M.S.[Mohammad Saadat],
Pose estimation of image sequence captured from urban environment,
PCVIA10(B:72).
PDF File. 1009
Feature tracking over long sequence, occlusions. BibRef

Kloihofer, W.[Werner], Kampel, M.[Martin],
Interest Point Based Tracking,
ICPR10(3549-3552).
IEEE DOI 1008
BibRef

Jalal, A.S.[Anand Singh], Tiwary, U.S.[Uma Shanker],
A Robust Object Tracking Method Using Structural Similarity in Daubechies Complex Wavelet Domain,
PReMI09(315-320).
Springer DOI 0912
Tracking using wavelet features. BibRef

Roy, S.D.[Sumantra Dutta], Tran, S.D.[Son Dinh], Davis, L.S.[Larry Steven], Vikram, B.S.[B. Sreenivasa],
Multi-resolution Tracking in Space and Time,
ICCVGIP08(352-358).
IEEE DOI 0812
Tracking through scale and orientation changes BibRef

Srikrishnan, V.[Viswanathan], Nagaraj, T.[Tadinada], Chaudhuri, S.[Subhasis],
Fragment Based Tracking for Scale and Orientation Adaptation,
ICCVGIP08(328-335).
IEEE DOI 0812
Tracking through scale and orientation changes BibRef

Mostafoui, G., Achard, C.[Catherine], Milgram, M.[Maurice],
Real time tracking of multiple persons using elementary tracks,
AVSBS05(129-134).
IEEE DOI 0602
BibRef
Earlier:
Objects Velocity Estimation on Images Sequences by Hough Transform with Projection (HTP),
ICPR04(III: 83-86).
IEEE DOI 0409
Hough, Motion. BibRef
Earlier:
Trajectories extraction from image sequences based on kinematic,
CIAP03(436-441).
IEEE DOI 0310
BibRef

Nam, S.[Siwook], Kim, H.[Hanjoo], Kim, J.H.[Jai-Hie],
Trajectory Estimation Based on Globally Consistent Homography,
CAIP03(214-221).
Springer DOI 0311
BibRef

Mukunoki, M.[Masayuki], Yasuda, K.[Kazutaka], Asada, N.[Naoki],
3D Model Generation from Image Sequences Using Global Geometric Constraint,
ISVC05(470-477).
Springer DOI 0512
BibRef

Amano, A.[Akira], Migita, T.[Tsuyoshi], Asada, N.[Naoki],
Stable Recovery of Shape and Motion from Partially Tracked Feature Points with Fast Nonlinear Optimization,
VI02(244).
PDF File. 0208
BibRef

Mery, D.[Domingo], Ochoa, F.[Felipe], Vidal, R.[René],
Tracking of Points in a Calibrated and Noisy Image Sequence,
ICIAR04(I: 647-654).
Springer DOI 0409
BibRef

Zhong, D., Chang, S.F.,
Long-term Moving Object Segmentation and Tracking Using Spatio-temporal Consistency,
ICIP01(II: 57-60).
IEEE DOI 0108
BibRef

Gibson, D.P.[David P.], Campbell, N.W.[Neill W.], Dalton, C.J.[Colin J.], Thomas, B.T.[Barry T.],
Extraction of Motion Data from Image Sequences to Assist Animators,
BMVC00(xx-yy).
PDF File. 0009
BibRef
And:
Visual Extraction of Motion-based Information from Image Sequences,
ICPR00(Vol III: 881-884).
IEEE DOI 0009
BibRef

Shum, H.Y.[Heung-Yeung], Ke, Q.F.[Qi-Fa], Zhang, Z.Y.[Zheng-You],
Efficient Bundle Adjustment with Virtual Key Frames: A Hierarchical Approach to Multi-frame Structure from Motion,
CVPR99(II: 538-543).
IEEE DOI BibRef 9900

Matei, B.[Bogdan], Meer, P.[Peter],
Optimal Rigid Motion Estimation and Performance Evaluation with Bootstrap,
CVPR99(I: 339-345).
IEEE DOI Award, CVPR, Student. BibRef 9900

Matei, B.[Bogdan], Meer, P.[Peter], Tyler, D.H.[David H.],
Performance Assessment by Resampling: Rigid Motion Estimators,
EEMTV98(xx) BibRef 9800

Carceroni, R.L.[Rodrigo L.], Kumar, A.[Ankita], Daniilidis, K.[Kostas],
Structure from Motion with Known Camera Positions,
CVPR06(I: 477-484).
IEEE DOI 0606
BibRef

Carceroni, R.L.[Rodrigo L.], Kutulakos, K.N.[Kiriakos N.],
Multi-View 3D Shape and Motion Recovery on the Spatio-Temporal Curve Manifold,
ICCV99(520-527).
IEEE DOI BibRef 9900

Carceroni, R.L.[Rodrigo L.], Kutulakos, K.N.[Kiriakos N.],
Toward Recovering Shape and Motion of 3D Curves from Multi-View Image Sequences,
CVPR99(I: 192-197).
IEEE DOI BibRef 9900
And:
Shape and Motion of 3-D Curves from Multi-View Image Scenes,
DARPA98(171-176). BibRef

Rehrmann, V.,
Object-oriented motion estimation in color image sequences,
ECCV98(I: 704).
Springer DOI BibRef 9800

Oakley, J.P., Powell, W.A.,
A Statistical Model for the Realiability of Motion Tracking Using Mean Normalised Correlation,
PERF96(XX-YY).
HTML Version. BibRef 9600

Ravela, S., Draper, B.A., Lim, J., and Weiss, R.,
Tracking Object Motion Across Aspect Changes for Augmented Reality,
ARPA96(1345-1352).
PS File. BibRef 9600
Earlier:
Adaptive Tracking and Model Registration Across Distinct Aspects,
IROS95(xx). BibRef
And: COINSTR 95-21, March 1995.
HTML Version. BibRef

Thonnessen, U., Ernst, D., Gross, H.,
Development of a Segment-Based Description of Events in Image Sequences,
ICPR92(I:383-386).
IEEE DOI BibRef 9200

Jacobs, D.W., Chennubhotla, C.,
Finding Structurally Consistent Motion Correspondences,
ICPR94(A:650-653).
IEEE DOI BibRef 9400

Benois-Pineau, J., Wu, L., Delanges, P., Barba, D.,
Motion and Structure Based Image Segmentation for Object-Oriented Time-Varying Sequences Coding,
ICPR94(A:733-735).
IEEE DOI BibRef 9400

Silven, O., Repo, T.,
Experiments with monocular visual tracking and environment modeling,
ICCV93(84-92).
IEEE DOI 0403
BibRef

Kim, Y.C., and Price, K.E.,
A Feature-Based Monocular Motion Analysis System Guided by Feedback Information,
CVPR93(744-745).
IEEE DOI BibRef 9300 USC Computer Vision BibRef
And: DARPA93(611-620). BibRef
Earlier:
Refinement of Noisy Correspondence Using Feedback from 3-D Motion,
CVPR92(836-838).
IEEE DOI BibRef
And: DARPA92(479-486). Use the motion estimate to determine the best matches for future frames and generate more complete 3-D structures. BibRef

Price, K.E., and Pavlin, I.,
Integration Effort in Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program,
DARPA88(417-422). BibRef 8800 USC Computer VisionResults of building a complete motion analysis system. Segmentation, matching and motion estimation. BibRef

Kabuka, M.[Mansur], and McVey, E.S.[Eugene S.],
Image Processing for Position Detection,
Draft1988. (UMiami and UVA) Extract the projection of the image and use the two 1-D functions to track an object. BibRef 8800

Narathong, C., Inigo, R.M., McVey, E.S.,
Motion-vision architectures,
CVPR88(411-416).
IEEE DOI 0403
BibRef

Inigo, R.M., Narathong, C., Doner, J.F., and McVey, E.S.,
A Fast Algorithm for Motion Prediction,
Draft1988. This seems to be a single scan line version of the projection paper above. BibRef 8800

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Region, Object, Target Tracking .


Last update:Mar 16, 2024 at 20:36:19