Target tracking based on incremental deep learning

	Target tracking based on incremental deep learning
	Cheng, S.; J.-X. Sun; Y.-G. Cao and L.-R. Zhao
	2015
发表期刊	Guangxue Jingmi Gongcheng/Optics and Precision Engineering
卷号	23 期号:4 页码:1161-1170
摘要	As current tracking algorithms lead to target drift or target loss in the complex environment, a tracking algorithm based on the incremental deep learning was proposed under a double-resampling particle filter framework. To solve the problem of particle degradation and depletion, the double-resampling method was introduced to adapt to the particle size in particle filtering and a Stacked Denoising Autoencoder(SDAE) was pre-trained by the unsupervised feature learning to alleviate the lack of training samples in visual tracking. Then, the SDAE was applied to online tracking, so that the extracted feature sets could express the region image representations of the particles effectively. The incremental feature learning was introduced to the encoder of SDAE, the feature sets were optimized by adding new features and merging the similar features to adapt to appearance changes of the moving object. Moreover, a support vector machine was used to classify the features then to improve the classification accuracy of the particles and to obtain a higher tracking precision. According to the results of experiments on variant challenging image sequences in the complex environment, the F-measure and the overlapping ratio of the presented algorithm are 94%, 74%, respectively and the average frame rate is 13 frame/s. Compared with the state-of-the-art tracking algorithms, the proposed method solves the problems of target drift and target loss efficiently and has better robust and higher accuracy, especially for the target in the occlusions, background clutter, illumination changes and appearance changes. , 2015, Chinese Academy of Sciences. All right reserved.
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/181722/56020
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.,J.-X. Sun,Y.-G. Cao and L.-R. Zhao. Target tracking based on incremental deep learning[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2015,23(4):1161-1170.
APA	Cheng, S.,J.-X. Sun,&Y.-G. Cao and L.-R. Zhao.(2015).Target tracking based on incremental deep learning.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,23(4),1161-1170.
MLA	Cheng, S.,et al."Target tracking based on incremental deep learning".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 23.4(2015):1161-1170.

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增量深度学习目标跟踪.caj（636KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览请求全文