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Visual tracking with online incremental deep learning and particle filter
Cheng, S.; Y. Cao; J. Sun and G. Liu
2015
发表期刊International Journal of Signal Processing, Image Processing and Pattern Recognition
卷号8期号:12页码:107-120
摘要To solve the problem of tracking the trajectory of a moving object and learning a deep compact image representation in the complex environment, a novel robust incremental deep learning tracker is presented under the particle filter framework. The incremental deep classification neural network was composed of stacked denoising autoencoder, incremental feature learning and support vector machine to achieve the feature- extracting and classification of particle set. Deep learning is successfully taken to express the image representations obtained effectively. Unsupervised feature learning is used to learn generic image features and transfer learning transforms knowledge from offline training to the online tracking process. The incremental feature learning was consisted of adding features and merging features to online learn compact feature set. Linear support vector machine increases the discretion for target with similar appearance and is further tuned to adapt to appearance changes of the moving object. Compared with the state-of-the-art trackers in the complex environment, the results of experiments on variant challenging image sequences show that incremental deep learning tracker solves the problem of existent trackers more efficiently, it has better robust and more accurate, especially for occlusions, background clutter, illumination changes and appearance changes. 2015 SERSC.
文章类型期刊论文
收录类别EI
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/56328
专题中科院长春光机所知识产出
推荐引用方式
GB/T 7714
Cheng, S.,Y. Cao,J. Sun and G. Liu. Visual tracking with online incremental deep learning and particle filter[J]. International Journal of Signal Processing, Image Processing and Pattern Recognition,2015,8(12):107-120.
APA Cheng, S.,Y. Cao,&J. Sun and G. Liu.(2015).Visual tracking with online incremental deep learning and particle filter.International Journal of Signal Processing, Image Processing and Pattern Recognition,8(12),107-120.
MLA Cheng, S.,et al."Visual tracking with online incremental deep learning and particle filter".International Journal of Signal Processing, Image Processing and Pattern Recognition 8.12(2015):107-120.
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