文献类型：期刊文献

英文题名：Object detection and tracking based on visual attention

作者：Zhang, Huawei[1]; Zhang, Qiaorong[1]

第一作者：张华伟

通讯作者：Zhang, Q.|[1048483301d73]张倩;[1048455a8f4d41]张琴;[1048443855eeb]张茜;[104845a8f4d41]张琴;

机构：[1] College of Computer and Information Engineering, Henan University of Economics and Law, No. 80, Wenhua Road, Zhengzhou 450002, China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]College of Computer and Information Engineering, Henan University of Economics and Law, No. 80, Wenhua Road, Zhengzhou 450002, China|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

年份：2012

卷号：6

期号：10

起止页码：2667-2671

外文期刊名：ICIC Express Letters

收录：EI(收录号：20124715687110);Scopus(收录号：2-s2.0-84869035197)

语种：英文

外文关键词：Algorithms - Computational methods - Security systems - Tracking (position) - Visualization

摘要：Object detection and tracking play an important role in some application fields such as intelligent surveillance, video analysis and content-based video retrieval. In this paper, an algorithm based on visual attention mechanism for object detection and tracking is proposed. Human visual attention mechanism is introduced in the proposed algorithm and a computational model of visual attention is constructed. Based on the computational model, visual saliency of each part in videos is computed. Salient objects are detected according to the visual saliency results. Using the color distribution model as the representation model of the object, objects are tracked by calculating the similarity of salient objects in the two successive frames. The algorithm has been tested on many video sequences. Experiment results and analysis are presented in this paper. The experimental results show that this algorithm is robust and it is effective and valid for object detection and tracking in videos. ? 2012 ISSN.