Volume 45 Issue 2
Apr.  2016
Article Contents

CHEN Shu, LIANG Wen-zhang. Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(2): 246-251.
Citation: CHEN Shu, LIANG Wen-zhang. Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(2): 246-251.

Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection

  • Publish Date: 2016-04-15
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    [2] ZHANG T, GHANEM B, LIU S, et al. Low-rank sparse learning for robust visual tracking[C]//European Conference on Computer Vision. Firenze, Italy: Springer-Verlag, 2012.
    [3] BAO C, WU Y, LING H, et al. Real time robust L1 tracker using accelerated proximal gradient approach[C]//IEEE Conference on Computer Vision and Pattern Recognition. Providence, RI, USA: IEEE, 2012.
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    [7] BABENKO B, YANG M, BELONGIE S. Robust object tracking with online multiple instance learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1619-1632.
    [8] KRIZHEVSKY A, SUTSKEVER I, HINTON G. ImageNet classification with deep convolutional neural networks[C]//Conference on Neural Information Processing Systems. Lake Tahoe, Nevada: MIT, 2012.
    [9] 郑胤, 陈权崎, 章毓晋. 深度学习及其在目标和行为识别中的新进展[J]. 中国图象图形学报, 2014, 19(2): 175-184. ZHENG Yin, CHEN Quan-qi, ZHANG Yu-jin. Deep learning and its new progress in object and behavior recognition[J]. Journal of Image and Graphics, 2014, 19(2): 175-184.
    [10] 李帅, 许悦雷, 马时平, 等. 一种深度神经网络SAR遮挡目标识别方法[J]. 西安电子科技大学学报(自然科学版), 2015, 42(3): 170-177. LI Shuai, XU Yue-lei, MA Shi-ping, et al. New method for SAR occluded targets recognition using DNN[J]. Journal of Xidian University, 2015, 42(3): 170-177.
    [11] VINCENT P, LAROCHELLE H, LAJOIE I, et al. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion[J]. Journal of Machine Learning Research, 2010, 11: 3371-3408.
    [12] ARULAMPALAM M S, MASKELL S, GORDON N. A tutorial on particle filters for online non-linear/non-Gaussian Bayesian tracking[J]. IEEE Transaction on Signal Processing, 2002, 50(1): 174-188.
    [13] KWON J, LEE K. Visual tracking decomposition[C]//IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, USA: IEEE, 2010.
    [14] BABENKO B, YANG M, BELONGIE S. Robust object tracking with online multiple instance learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1619-1632.
    [15] EVERINGHAM M, VAN GOOL L, WILLIAMS C, et al. The Pascal visual object classes (voc) challenge[J]. International Journal of Computer Vision, 2010, 88(2): 303-338.
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Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection

CHEN Shu, LIANG Wen-zhang. Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(2): 246-251.
Citation: CHEN Shu, LIANG Wen-zhang. Object Tracking by Combining Feature Correspondences Matching with Deep Neural Network Detection[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(2): 246-251.
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