标题:PERSON RE-IDENTIFICATION BY FREE ENERGY SCORE SPACE ENCODING
作者:Zhao, Yanna; Zhao, Xu; Liu, Yuncai
通讯作者:Zhao, YN
作者机构:[Zhao, Yanna] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.; [Zhao, Xu; Liu, Yuncai] Shanghai Jiao Tong Univ, Sch Elect Inf 更多
会议名称:IEEE International Conference on Image Processing (ICIP)
会议日期:OCT 27-30, 2014
来源:2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
出版年:2014
页码:2452-2456
关键词:person re-identification; appearance modeling; Gaussian Mixture Model;; free energy score space
摘要:Person re-identification is an important and challenging computer vision problem. Recent progress in this area is due to new visual features and models that deals with crossview variations. Instead of working towards more complex models, we focus on low level features and their encoding. Low level features capturing the color and structural information are first extracted from human images. Gaussian Mixture Model (GMM) is then employed to approximate the distribution of the features, providing a relatively comprehensive statistical representation. Finally, low level features are mapped to a space by computing free energy score of the GMM. The mapped features are encoded into a fixed-length feature vector for person re-identification. Extensive experiments are conducted on several public datasets. Comparisons with benchmark person re-identification methods show the promising performance of our approach.
收录类别:CPCI-S
资源类型:会议论文
TOP