Fast compressive tracking with robust example selection based on multiple instance learning in smart and autonomous systems

This article has been withdrawn at the request of the editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. This error bears no reflection on the article or its authors. The publisher apologizes to the authors and the readers for this unfortunate error. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy .

[1]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[2]  D. M. Titterington,et al.  Comment on “On Discriminative vs. Generative Classifiers: A Comparison of Logistic Regression and Naive Bayes” , 2008, Neural Processing Letters.

[3]  James T. Kwok,et al.  Online multiple instance learning with no regret , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Xue-Jie Zhang,et al.  Enhanced fast compressive tracking based on adaptive measurement matrix , 2015, IET Comput. Vis..

[5]  T. Poggio,et al.  Regularized Least-Squares Classification 133 In practice , although , 2007 .

[6]  Jing Peng,et al.  SVM vs regularized least squares classification , 2004, ICPR 2004.

[7]  Silvio Savarese,et al.  Robust real-time tracking combining 3D shape, color, and motion , 2016, Int. J. Robotics Res..

[8]  Li Bai,et al.  Real-Time Probabilistic Covariance Tracking With Efficient Model Update , 2012, IEEE Transactions on Image Processing.

[9]  Kaihua Zhang,et al.  Real-time visual tracking via online weighted multiple instance learning , 2013, Pattern Recognit..

[10]  Ming-Hsuan Yang,et al.  Object Tracking Benchmark , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Rui Caseiro,et al.  High-Speed Tracking with Kernelized Correlation Filters , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Ming-Hsuan Yang,et al.  Robust Object Tracking with Online Multiple Instance Learning , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Qianqing Qin,et al.  Adaptive weighted real-time compressive tracking , 2014, IET Comput. Vis..

[14]  Carsten Rother,et al.  Learning discriminative localization from weakly labeled data , 2014, Pattern Recognit..

[15]  Zhuowen Tu,et al.  Weakly supervised histopathology cancer image segmentation and classification , 2014, Medical Image Anal..

[16]  Thomas G. Dietterich,et al.  Solving the Multiple Instance Problem with Axis-Parallel Rectangles , 1997, Artif. Intell..

[17]  Gordon Morison,et al.  Extended fast compressive tracking with weighted multi-frame template matching for fast motion tracking , 2016, Pattern Recognit. Lett..

[18]  Shai Avidan,et al.  Ensemble Tracking , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Lei Zhang,et al.  Real-Time Object Tracking Via Online Discriminative Feature Selection , 2013, IEEE Transactions on Image Processing.

[20]  Zhuowen Tu,et al.  Feature Mining for Image Classification , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Huchuan Lu,et al.  Visual tracking via adaptive structural local sparse appearance model , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[22]  Paul A. Viola,et al.  Multiple Instance Boosting for Object Detection , 2005, NIPS.

[23]  Lei Zhang,et al.  Fast Compressive Tracking , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Ming-Hsuan Yang,et al.  Visual tracking with online Multiple Instance Learning , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Andrea Cavallaro,et al.  Accepted for Publication in Ieee Transactions on Image Processing Adaptive Appearance Modeling for Video Tracking: Survey and Evaluation , 2022 .

[26]  D. Freedman,et al.  Asymptotics of Graphical Projection Pursuit , 1984 .

[27]  Wolfgang Nejdl,et al.  Introduction to the special section on twitter and microblogging services , 2013, TIST.

[28]  Huchuan Lu,et al.  Robust object tracking via sparsity-based collaborative model , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[29]  Rui Caseiro,et al.  Exploiting the Circulant Structure of Tracking-by-Detection with Kernels , 2012, ECCV.

[30]  R. Collins,et al.  On-line selection of discriminative tracking features , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[31]  Horst Bischof,et al.  Real-Time Tracking via On-line Boosting , 2006, BMVC.

[32]  Yanxi Liu,et al.  Online Selection of Discriminative Tracking Features , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[34]  Luc Van Gool,et al.  The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.

[35]  Zhongfei Zhang,et al.  A survey of appearance models in visual object tracking , 2013, ACM Trans. Intell. Syst. Technol..

[36]  Shai Avidan Ensemble Tracking , 2007, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Erik Blasch,et al.  Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT) , 2011 .

[38]  Lei Zhang,et al.  Real-Time Compressive Tracking , 2012, ECCV.