Synergetic Object Recognition Based on Visual Attention Saliency Map

摘要：

To study the object recognition in complex scene, a synergetic object recognition algorithm based on visual attention saliency map is proposed in the paper. We utilize the feature of the object extracted by PCA as the prototype vector of the synergetic pattern recognition. The adjoint vector is calculated through the synergetic learning algorithm. Then, the salient locations of the scene image including learned objects are selected through the visual attention saliency map. At last, the object in the salient location is recognized through the synergetic pattern recognition. The validity of the algorithm is demonstrated by the experiments.

作者: Jing Shao Jun Gao Jing Yang

作者单位: Dept. of Computer and Information Hefei University of Technology Hefei, Anhui Province, China Center for Biomimetic Sensing and Control Research Institute of Intelligent Machines, Chinese Academ

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 660-665

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）