RGB-D based multi-attribute people search in intelligent visual surveillance

Authors:
Wu Liu;Tian Xia;Ji Wan;Yongdong Zhang;Jintao Li
Affiliations:
Institute of Computing Technology, Chinese Academy of Science, Beijing, China;Institute of Computing Technology, Chinese Academy of Science, Beijing, China;Institute of Computing Technology, Chinese Academy of Science, Beijing, China;Institute of Computing Technology, Chinese Academy of Science, Beijing, China;Institute of Computing Technology, Chinese Academy of Science, Beijing, China
Venue:
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Year:
2012

Citing 7
Cited 0

Statistical color models with application to skin detection

International Journal of Computer Vision
Unified video annotation via multigraph learning

IEEE Transactions on Circuits and Systems for Video Technology
Multiview spectral embedding

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Real-time human pose recognition in parts from single depth images

CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Image ranking and retrieval based on multi-attribute queries

CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Indexing and matching multiple-attribute strings for efficient multimedia query processing

IEEE Transactions on Multimedia
A survey on visual surveillance of object motion and behaviors

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

Quantified Score

Hi-index	0.00

Visualization

Abstract

Searching people in surveillance videos is a typical task in intelligent visual surveillance (IVS). However, current IVS techniques can hardly handle multi-attribute queries, which is a natural way of finding people in real-world. The challenges arise from the extraction of multiple attributes which largely suffer from illumination change, shadow and complicated background in the real-world surveillance environments. In this paper, we investigate how these challenges can be addressed when IVS is equipped with RGB-D information obtained by an RGB-D camera. With the RGB-D information, we propose methods that accurately and robustly segment human region and extract three groups of attributes including biometrical attributes, appearance attributes and motion attributes. Furthermore, we introduce a novel IVS system which is capable of handling multi-attribute queries for searching people in surveillance videos. Experimental evaluations demonstrate the effectiveness of the proposed method and system, and also the promising applications of bringing RGB-D information into IVS.