Literature DB >> 15641735

Support vector tracking.

Shai Avidan1.   

Abstract

Support Vector Tracking (SVT) integrates the Support Vector Machine (SVM) classifier into an optic-flow-based tracker. Instead of minimizing an intensity difference function between successive frames, SVT maximizes the SVM classification score. To account for large motions between successive frames, we build pyramids from the support vectors and use a coarse-to-fine approach in the classification stage. We show results of using SVT for vehicle tracking in image sequences.

Mesh:

Year:  2004        PMID: 15641735     DOI: 10.1109/TPAMI.2004.53

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  21 in total

1.  Enforcing Convexity for Improved Alignment with Constrained Local Models.

Authors:  Yang Wang; Simon Lucey; Jeffrey F Cohn
Journal:  Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit       Date:  2008-06-23

2.  Non-rigid Face Tracking with Local Appearance Consistency Constraint.

Authors:  Yang Wang; Simon Lucey; Jeffrey F Cohn; Jason Saragih
Journal:  Image Vis Comput       Date:  2010-05       Impact factor: 2.818

3.  Object Tracking Based On Huber Loss Function.

Authors:  Yong Wang; Shiqiang Hu; Shandong Wu
Journal:  Vis Comput       Date:  2018-05-24       Impact factor: 2.601

4.  A practical evaluation of correlation filter-based object trackers with new features.

Authors:  Islam Mohamed; Ibrahim Elhenawy; Ahmed W Sallam; Andrew Gatt; Ahmad Salah
Journal:  PLoS One       Date:  2022-08-25       Impact factor: 3.752

5.  Learning based particle filtering object tracking for visible-light systems.

Authors:  Wei Sun
Journal:  Optik (Stuttg)       Date:  2015-05-15       Impact factor: 2.443

6.  A Kinect-based real-time compressive tracking prototype system for amphibious spherical robots.

Authors:  Shaowu Pan; Liwei Shi; Shuxiang Guo
Journal:  Sensors (Basel)       Date:  2015-04-08       Impact factor: 3.576

7.  Object tracking using adaptive covariance descriptor and clustering-based model updating for visual surveillance.

Authors:  Lei Qin; Hichem Snoussi; Fahed Abdallah
Journal:  Sensors (Basel)       Date:  2014-05-26       Impact factor: 3.576

8.  A novel tracking algorithm via feature points matching.

Authors:  Nan Luo; Quansen Sun; Qiang Chen; Zexuan Ji; Deshen Xia
Journal:  PLoS One       Date:  2015-01-24       Impact factor: 3.240

Review 9.  Image processing and recognition for biological images.

Authors:  Seiichi Uchida
Journal:  Dev Growth Differ       Date:  2013-04-07       Impact factor: 2.053

10.  Incremental structured dictionary learning for video sensor-based object tracking.

Authors:  Ming Xue; Hua Yang; Shibao Zheng; Yi Zhou; Zhenghua Yu
Journal:  Sensors (Basel)       Date:  2014-02-17       Impact factor: 3.576

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