Multi-target visual tracking and occlusion detection by combining Bhattacharyya Coefficient and Kalman filter innovation

This paper introduces an approach for visual tracking of multi-target with occlusion occurrence. Based on the author’s previous work in which the Overlap Coefficient (OC) is used to detect the occlusion, in this paper a method of combining Bhattacharyya Coefficient (BC) and Kalman filter innovation term is proposed as the criteria for jointly detecting the occlusion occurrence. Fragmentation of target is introduced in order to closely monitor the occlusion development. In the course of occlusion, the Kalman predictor is applied to determine the location of the occluded target, and the criterion for checking the re-appearance of the occluded target is also presented. The proposed approach is put to test on a standard video sequence, suggesting the satisfactory performance in multi-target tracking.     

基于数据挖掘的高职教学质量监控评价系统设计及应用

文章对高职教学质量监控评价系统进行了需求分析、功能分析、结构设计及数据库设计等4个方面进行分析设计,以数据挖掘技术在高职教学质量监控评价系统中数据挖掘运用进行分析,帮助教育管理者做出正确的分析和决策,促进高等职业教育实现现代化。