16.6.2.6 Target Tracking, Multi-Point Tracking, Corners, Features

Chapter Contents (Back)
Multi-Target Tracking. Multi-Point Tracking. 1301

Cox, I.J., and Miller, M.L.,
On Finding Ranked Assignments with Application to Multi-Target Tracking and Motion Correspondence,
AeroSys(32), No. 1, January 1995, pp. 486-489. BibRef 9501

Cox, I.J., Hingorani, S.L.,
An Efficient Implementation of Reid's Multiple Hypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking,
PAMI(18), No. 2, February 1996, pp. 138-150.
IEEE DOI BibRef 9602
Earlier:
An Efficient Implementation and Evaluation of Reid's Multiple Hypothesis Tracking Algorithm for Visual Tracking,
ICPR94(A:437-442).
IEEE DOI For Reid:
See also Algorithm for Tracking Multiple Targets, An. Track (in the image plane) a large nubmer of corner features through an image sequence. BibRef

Shen, X.Q.[Xin-Quan], Palmer, P.[Phil],
Uncertainty Propagation and the Matching of Junctions as Feature Groupings,
PAMI(22), No. 12, December 2000, pp. 1381-1395.
IEEE DOI 0012
In tracking use topology of junctions based on groupings of features which are related to an object. BibRef

Micheloni, C.[Christian], Foresti, G.L.[Gian Luca],
A robust feature tracker for active surveillance of outdoor scenes,
ELCVIA(1), No. 1 2002, pp. 21-34.
DOI Link BibRef 0200
Earlier:
Focusing on Target's Features while Tracking,
ICPR06(I: 836-839).
IEEE DOI 0609
BibRef
Earlier:
Zoom on Target While Tracking,
ICIP05(III: 117-120).
IEEE DOI 0512
Track features, compensate for background changes due to camera motion (
See also Generalized Image Matching by the Method of Differences. ) BibRef

Veenman, C.J., Reinders, M.J.T., Backer, E.,
Motion tracking as a constrained optimization problem,
PR(36), No. 9, September 2003, pp. 2049-2067.
Elsevier DOI 0307
BibRef

Veenman, C.J., Reinders, M.J.T., Backer, E.,
Establishing motion correspondence using extended temporal scope,
AI(145), No. 1-2, April 2003, pp. 227-243.
Elsevier DOI Feature point matching. 0306
BibRef

Dorini, L.B.[Leyza Baldo], Goldenstein, S.K.[Siome Klein],
Unscented feature tracking,
CVIU(115), No. 1, January 2011, pp. 8-15.
Elsevier DOI 1011
Feature tracking; Uncertainty tracking; Outlier rejection; Statistical correspondences BibRef

Gouiffès, M.[Michèle], Collewet, C.[Christophe], Fernandez-Maloigne, C.[Christine], Trémeau, A.[Alain],
A study on local photometric models and their application to robust tracking,
CVIU(116), No. 8, August 2012, pp. 896-907.
Elsevier DOI 1205
BibRef
Earlier:
A Photometric Model for Specular Highlights and Lighting Changes. Application to Feature Points Tracking.,
ICIP06(2117-2120).
IEEE DOI 0610
BibRef
Earlier:
Feature Points Tracking: Robustness to Specular Highlights and Lighting Changes,
ECCV06(IV: 82-93).
Springer DOI 0608
Robust feature point tracking; Local photometric models BibRef

Collewet, C.[Christophe], Marchand, E.[Eric],
Modeling complex luminance variations for target tracking,
CVPR08(1-7).
IEEE DOI 0806
BibRef

Kermad, C., Collewet, C.[Christophe],
Improving Feature Tracking by Robust Points of Interest Selection,
VMV01(xx-yy).
PDF File. 0209
BibRef

Gouiffes, M.[Michele],
Tracking by Combining Photometric Normalization and Color Invariants According to their Relevance,
ICIP07(VI: 145-148).
IEEE DOI 0709
BibRef

Fan, J.L.[Jia-Lue], Shen, X.H.[Xiao-Hui], Wu, Y.[Ying],
Scribble Tracker: A Matting-Based Approach for Robust Tracking,
PAMI(34), No. 8, August 2012, pp. 1633-1644.
IEEE DOI 1206
BibRef
Earlier:
Closed-Loop Adaptation for Robust Tracking,
ECCV10(I: 411-424).
Springer DOI 1009
Model updating in tracking. Get accurate boundaries of the target. BibRef

Fan, J.L.[Jia-Lue], Wu, Y.[Ying],
Contextual saliency,
VCIP11(1-4).
IEEE DOI 1201
BibRef
Earlier: A2, A1:
Contextual flow,
CVPR09(33-40).
IEEE DOI 0906
Feature point tracking. BibRef

Bins, J.[Jose], Dihl, L.L.[Leandro L.], Jung, C.R.[Claudio R.],
Target Tracking Using Multiple Patches and Weighted Vector Median Filters,
JMIV(45), No. 3, March 2013, pp. 293-307.
Springer DOI 1301
Separate patches on one target. Track each patch, fuse results with WVM BibRef

Fickel, G.P.[Guilherme P.], Jung, C.R.[Claudio R.], Lee, B.[Bowon],
Multiview image and video interpolation using weighted vector median filters,
ICIP14(5387-5391)
IEEE DOI 1502
Cameras BibRef

Babu, R.V.[R. Venkatesh], Parate, P.[Priti], Acharya K., Ä.[Äniruddha],
Robust tracking with interest points: A sparse representation approach,
IVC(33), No. 1, 2015, pp. 44-56.
Elsevier DOI 1402
Visual tracking BibRef

Babu, R.V.[R. Venkatesh], Parate, P.[Priti],
Interest points based object tracking via sparse representation,
ICIP13(2963-2967)
IEEE DOI 1402
Harris corner BibRef

Babu, R.V.[R. Venkatesh],
Real-time robust tracking via sparse representation: A mode-seeking approach,
ICIP13(3919-3923)
IEEE DOI 1402
Likelihood Map
See also Online adaptive radial basis function networks for robust object tracking. BibRef

Kumar, M.S.N.[M.S. Naresh], Parate, P.[Priti], Babu, R.V.[R. Venkatesh],
Fragment-based real-time object tracking: A sparse representation approach,
ICIP12(433-436).
IEEE DOI 1302
BibRef

Rabbi, I.[Ihsan], Ullah, S.[Sehat], Javed, M.[Muhammad], Zen, K.[Kartinah],
Analysing the attributes of fiducial markers for robust tracking in augmented reality applications,
IJCVR(7), No. 1/2, 2017, pp. 68-82.
DOI Link 1701
BibRef

Roudot, P., Ding, L., Jaqaman, K., Kervrann, C., Danuser, G.,
Piecewise-Stationary Motion Modeling and Iterative Smoothing to Track Heterogeneous Particle Motions in Dense Environments,
IP(26), No. 11, November 2017, pp. 5395-5410.
IEEE DOI 1709
Kalman filters, Optimization, Particle tracking, Signal to noise ratio, Tracking, Trajectory, Multiple particle tracking (MPT), adaptive gating, cell biology, interacting multiple model, kalman smoothing BibRef

Wang, J.[Jun], Wang, Y.Y.[Yuan-Yun], Wang, H.Z.[Han-Zi],
Adaptive Appearance Modeling With Point-to-Set Metric Learning for Visual Tracking,
CirSysVideo(27), No. 9, September 2017, pp. 1987-2000.
IEEE DOI 1709
Robustness, Target tracking, Visualization, Affine hull (AH), appearance model, metric learning. BibRef

Wang, J.[Jun], Yin, P.[Peng], Wang, Y.Y.[Yuan-Yun], Yang, W.H.[Wen-Hui],
CMAT: Integrating Convolution Mixer and Self-Attention for Visual Tracking,
MultMed(26), 2024, pp. 326-338.
IEEE DOI 2401
BibRef

Jung, H.W.[Hye-Won], Lee, S.H.[Sang-Heon], Donnelley, M.[Martin], Parsons, D.[David], Stamatescu, V.[Victor], Lee, I.[Ivan],
Multiple particle tracking in time-lapse synchrotron X-ray images using discriminative appearance and neighbouring topology learning,
PR(93), 2019, pp. 485-497.
Elsevier DOI 1906
Convolutional neural network (CNN), LDA, Neighbuoring topology, Multi-frame association, Particle tracking BibRef

Zhang, S., Zhao, X., Fang, L.,
CAT: Corner Aided Tracking With Deep Regression Network,
MultMed(23), 2021, pp. 859-870.
IEEE DOI 2103
Target tracking, Shape, Estimation, Cats, Strain, Reliability, Training, Corner aided tracker, deep regression tracking, visual object tracking BibRef

Xu, Z.B.[Zhen-Bo], Yang, W.[Wei], Zhang, W.[Wei], Tan, X.[Xiao], Huang, H.[Huan], Huang, L.S.[Liu-Sheng],
Segment as Points for Efficient and Effective Online Multi-Object Tracking and Segmentation,
PAMI(44), No. 10, October 2022, pp. 6424-6437.
IEEE DOI 2209
Image color analysis, Feature extraction, Image segmentation, Automobiles, Motion segmentation, Annotations, Object segmentation, tracking BibRef

Xu, Z.B.[Zhen-Bo], Zhang, W.[Wei], Tan, X.[Xiao], Yang, W.[Wei], Huang, H.[Huan], Wen, S.L.[Shi-Lei], Ding, E.R.[Er-Rui], Huang, L.S.[Liu-Sheng],
Segment as Points for Efficient Online Multi-object Tracking and Segmentation,
ECCV20(I:264-281).
Springer DOI 2011
BibRef

Gao, Y.[Yan], Xu, H.J.[Hao-Jun], Zheng, Y.[Yu], Li, J.[Jie], Gao, X.B.[Xin-Bo],
An Object Point Set Inductive Tracker for Multi-Object Tracking and Segmentation,
IP(31), 2022, pp. 6083-6096.
IEEE DOI 2210
Task analysis, Tracking, Image segmentation, Feature extraction, Training, Multitasking, Multi-object tracking and segmentation, multi-object tracking BibRef

Liu, C.W.[Chong-Wei], Li, H.J.[Hao-Jie], Wang, Z.H.[Zhi-Hui], Xu, R.[Rui],
Addressing Challenges of Incorporating Appearance Cues Into Heuristic Multi-Object Tracker via a Novel Feature Paradigm,
IP(33), 2024, pp. 5727-5739.
IEEE DOI 2410
Feature extraction, Tracking, Costs, Trajectory, Training, Robustness, Runtime, Computational modeling, Benchmark testing, Detectors, feature similarity BibRef


Yoon, S.[Sungjoon], Shim, K.J.[Kyu-Jin], Park, K.[Kayoung], Kim, C.[Changick],
Weakly-Supervised Multiple Object Tracking Via A Masked Center Point Warping Loss,
ICIP21(1164-1168)
IEEE DOI 2201
Training, Measurement, Image processing, Object detection, Object tracking, Multiple object tracking, Weakly-supervised learning BibRef

Mohamed, S.A.S.[Sherif A. S.], Yasin, J.N.[Jawad N.], Haghbayan, M.H.[Mohammad-Hashem], Miele, A.[Antonio], Heikkonen, J.[Jukka], Tenhunen, H.[Hannu], Plosila, J.[Juha],
Asynchronous Corner Tracking Algorithm Based on Lifetime of Events for Davis Cameras,
ISVC20(I:530-541).
Springer DOI 2103
BibRef

Vlaminck, M., Luong, H., Philips, W.,
A markerless 3D tracking approach for augmented reality applications,
IC3D17(1-7)
IEEE DOI 1804
SLAM (robots), augmented reality, cameras, image motion analysis, object detection, object tracking, pose estimation, robot vision, registration BibRef

Zeng, X., Xu, L., Ma, L., Zhao, R.,
Interest points based collaborative tracking,
VCIP16(1-4)
IEEE DOI 1701
Collaboration BibRef

Stylianou, A., Pless, R.[Robert],
SparkleGeometry: Glitter Imaging for 3D Point Tracking,
CCD16(919-926)
IEEE DOI 1612
BibRef

Dimitriou, N., Stavropoulos, G., Moustakas, K., Tzovaras, D.,
Multiple object tracking based on motion segmentation of point trajectories,
AVSS16(200-206)
IEEE DOI 1611
Clustering algorithms BibRef

Pancham, A.[Ardhisha], Withey, D.[Daniel], Bright, G.[Glen],
Tracking image features with PCA-SURF descriptors,
MVA15(365-368)
IEEE DOI 1507
Accuracy. Which features to track. BibRef

Kumar, K.A.S.[K.A. Shiva], Ramakrishnan, K.R., Rathna, G.N.,
Distributed sigma point information filters for target tracking in camera networks,
MVA15(373-377)
IEEE DOI 1507
Cameras BibRef

Piccini, T.[Tommaso], Persson, M.[Mikael], Nordberg, K.[Klas], Felsberg, M.[Michael], Mester, R.[Rudolf],
Good Edgels to Track: Beating the Aperture Problem with Epipolar Geometry,
CVRoads14(652-664).
Springer DOI 1504
Sparsity of the matched key-points in multi-view stereo, motion. Edgels that can be used with motion constraints. BibRef

Maresca, M.E.[Mario Edoardo], Petrosino, A.[Alfredo],
Clustering Local Motion Estimates for Robust and Efficient Object Tracking,
VOT14(244-253).
Springer DOI 1504
BibRef
And:
The Matrioska Tracking Algorithm on LTDT2014 Dataset,
LTDT14(720-725)
IEEE DOI 1409
BibRef
Earlier:
MATRIOSKA: A Multi-level Approach to Fast Tracking by Learning,
CIAP13(II:419-428).
Springer DOI 1309
Video tracking using multiple keypoint extraction methods. BibRef

Lourenço, M.[Miguel], Barreto, J.P.[João Pedro],
Tracking Feature Points in Uncalibrated Images with Radial Distortion,
ECCV12(IV: 1-14).
Springer DOI 1210
BibRef

Zheng, H.[Hong], Sui, Q.Q.[Qiang-Qiang], Wasfy, W., Chen, L.[Lei],
A New Method for the Discerning of Point Moving Targets' Tracks,
CISP09(1-5).
IEEE DOI 0910
BibRef

Tian, Y.X.[Yi-Xiang], Gerke, M.[Markus], Vosselman, G.[George], Zhu, Q.[Qing],
Automatic Edge Matching Across an Image Sequence Based on Reliable Points,
ISPRS08(B3b: 657 ff).
PDF File. 0807
BibRef

Buchanan, A.[Aeron], Fitzgibbon, A.W.[Andrew W.],
Combining local and global motion models for feature point tracking,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Hernandez, S.[Sergio], Teal, P.[Paul],
Multi-target Tracking with Poisson Processes Observations,
PSIVT07(474-483).
Springer DOI 0712
BibRef

Tsin, Y.H.[Yang-Hai], Genc, Y.[Yakup], Zhu, Y.[Ying], Ramesh, V.[Visvanathan],
Learn to Track Edges,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Domae, Y., Takauji, H., Stier, H., Kaneko, S., Tanaka, T.,
Extraction and tracking of orientation coded features being robust against illumination changes,
IEVM06(xx-yy).
PDF File. 0609
BibRef

Šegvic, S.[Siniša], Remazeilles, A.[Anthony], Chaumette, F.[François],
Enhancing the Point Feature Tracker by Adaptive Modelling of the Feature Support,
ECCV06(II: 112-124).
Springer DOI 0608
BibRef

Fiala, M.,
Using Normalized Interest Point Trajectories Over Scale for Image Search,
CRV06(58-58).
IEEE DOI 0607
Track interest points (corners). BibRef

Mohanna, F., Mokhtarian, F.,
Robust corner tracking for multimedia applications,
ICIP02(III: 945-948).
IEEE DOI 0210
BibRef
And:
A Multi-Scale Approach to Corner Tracking,
WSCG02(SH-74).
HTML Version. 0209

See also Performance evaluation of corner detectors using consistency and accuracy measures. BibRef

Brantner, S.[Stefan], Auer, T.[Thomas], Pinz, A.[Axel],
Real-Time Optical Edge and Corner Tracking at Subpixel Accuracy,
CAIP99(534-541).
Springer DOI 9909
BibRef

Gu, H., Asada, M., and Shirai, Y.,
The Optimal Partition of Moving Edge Segments,
CVPR93(367-372).
IEEE DOI
See also MDL-Based Segmentation and Motion Modeling in a Long Image Sequence of Scene with Multiple Independently Moving-Objects. Using MDL coding, find moving edges. BibRef 9300

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


Last update:Oct 22, 2024 at 22:09:59