Multiobject Tracking by Submodular Optimization

In this paper, we propose a new multiobject visual tracking algorithm by submodular optimization. The proposed algorithm is composed of two main stages. At the first stage, a new selecting strategy of tracklets is proposed to cope with occlusion problem. We generate low-level tracklets using overlap criteria and min-cost flow, respectively, and then integrate them into a candidate tracklets set. In the second stage, we formulate the multiobject tracking problem as the submodular maximization problem subject to related constraints. The submodular function selects the correct tracklets from the candidate set of tracklets to form the object trajectory. Then, we design a connecting process which connects the corresponding trajectories to overcome the occlusion problem. Experimental results demonstrate the effectiveness of our tracking algorithm.<xref ref-type="fn" rid="fn1"><sup>1</sup></xref><fn id="fn1"><label><sup>1</sup></label><p>Our source code is available at <uri>https://github.com/shenjianbing/submodulartrack</uri>.</p></fn>

[1]  Afshin Dehghan,et al.  GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs , 2012, ECCV.

[2]  Ling Shao,et al.  Generalized Pooling for Robust Object Tracking , 2016, IEEE Transactions on Image Processing.

[3]  Bernt Schiele,et al.  Monocular 3D pose estimation and tracking by detection , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Ming Yang,et al.  Regionlets for Generic Object Detection , 2013, 2013 IEEE International Conference on Computer Vision.

[5]  Afshin Dehghan,et al.  Target Identity-aware Network Flow for online multiple target tracking , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Fabio Tozeto Ramos,et al.  Alextrac: Affinity learning by exploring temporal reinforcement within association chains , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[7]  Afshin Dehghan,et al.  GMMCP tracker: Globally optimal Generalized Maximum Multi Clique problem for multiple object tracking , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[8]  Xuelong Li,et al.  Linear Tracking for 3-D Medical Ultrasound Imaging , 2013, IEEE Transactions on Cybernetics.

[9]  David A. McAllester,et al.  Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Mohamed R. Amer,et al.  Multiobject tracking as maximum weight independent set , 2011, CVPR 2011.

[11]  Ling Shao,et al.  Video Salient Object Detection via Fully Convolutional Networks , 2017, IEEE Transactions on Image Processing.

[12]  Mario Sznaier,et al.  The Way They Move: Tracking Multiple Targets with Similar Appearance , 2013, 2013 IEEE International Conference on Computer Vision.

[13]  Francesco Solera,et al.  Learning to Divide and Conquer for Online Multi-target Tracking , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[14]  Pascal Fua,et al.  Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Multiple Object Tracking Using K-shortest Paths Optimization , 2022 .

[15]  Xuelong Li,et al.  Lazy Random Walks for Superpixel Segmentation , 2014, IEEE Transactions on Image Processing.

[16]  Ivan Laptev,et al.  On pairwise costs for network flow multi-object tracking , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Ruigang Yang,et al.  Saliency-Aware Video Object Segmentation , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Ramakant Nevatia,et al.  Global data association for multi-object tracking using network flows , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[19]  Pietro Perona,et al.  Fast Feature Pyramids for Object Detection , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Larry S. Davis,et al.  Submodular Salient Region Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Wenguan Wang,et al.  Occlusion-Aware Real-Time Object Tracking , 2017, IEEE Transactions on Multimedia.

[22]  James M. Rehg,et al.  Gaze-enabled egocentric video summarization via constrained submodular maximization , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Ling Shao,et al.  Submodular Object Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  Konrad Schindler,et al.  Continuous Energy Minimization for Multitarget Tracking , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Jianbing Shen,et al.  Fast Online Tracking With Detection Refinement , 2018, IEEE Transactions on Intelligent Transportation Systems.

[26]  Charless C. Fowlkes,et al.  Globally-optimal greedy algorithms for tracking a variable number of objects , 2011, CVPR 2011.

[27]  Stefan Roth,et al.  MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking , 2015, ArXiv.

[28]  Ling Shao,et al.  Visual Tracking Under Motion Blur , 2016, IEEE Transactions on Image Processing.

[29]  Konrad Schindler,et al.  Detection- and Trajectory-Level Exclusion in Multiple Object Tracking , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[30]  Rama Chellappa,et al.  Entropy-Rate Clustering: Cluster Analysis via Maximizing a Submodular Function Subject to a Matroid Constraint , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .