A Novel System for Video Retrieval of Frontal-View Indoor Moving Pedestrians
This paper presents a solution for video retrieval of frontal-view indoor moving pedestrians. A novel and effective system which contains two parts, feature extraction and key frame sets matching, is proposed. For the first part, a successful fusion strategy is proposed for effectively combining information from color and texture features. The experiment indicates that the retrieval accuracy based on this fusion method is better than only using either of color feature or texture feature. In another part of key frame sets matching, this paper tries to solve the problem from the view of the subspace method. The latest and novel subspace method of Discriminative Canonical Correlations (DCC) is adopted. In the experiment, compared with other two classical subspace methods (MSM and CMSM), the DCC method distinctly outperforms them in terms of retrieval accuracy.
Shuo Li Yu-Jin Zhang
Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
378-383
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）