文章基本信息

标题：Multi-target Tracking based on Level Set Segmentation and Contextual Information
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作者：Liu Meng ; Qingxuan Jia
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2013
卷号：6
期号：4
出版社：SERSC
摘要：In the unconstrained environment for video tracking is essential for many applications, such as video surveillance, man-machine interaction. In fact, moving object in the sequences generally has the context information of others or the different moments of its own state. Our research focus on the complex scenes, tracking multiple articulated targets, obtaining the features of the target, getting the precise target segmentation and improving the accuracy and reliability of tracking. We propose using top-down segmentation to feedback object detection, also contains the shape information. And the local appearance information is embedded into the framework of the level set. Then we propose a method to solve the interference of similar appearance target and multi-target tracking, by using context information to create two auxiliary items: Misleading items and support items. Both of them are using continuous random ferns. We experimentally evaluate our proposed approach on challenging sequences and video in real-world demonstrate its good performance in practice.
关键词：target segmentation; multi-target tracking; level set; context information; random ferns