Title
Foreground regions extraction and characterization towards real-time object tracking
Abstract
Object localization and tracking are key issues in the analysis of scenes for video surveillance or scene understanding applications. This paper presents a contribution to the object tracking task in indoor environments surveyed by multiple fixed cameras. The method proposed uses a foreground separation process at each camera view. Then, a 3D-foreground scene is modeled and discretized into voxels making use of all the segmented views, preventing the difficulties of inter-object occlusions in 2D trackers, and increasing the robustness for not having to rely only in one view. The voxels are grouped into meaningful blobs, whose colors are modeled for tracking purposes, using a novel voxel-coloring technique that considers possible inter/intra-object occlusions. Finally, color information together with other characteristic features of 3D object appearances are temporally tracked using a template-based technique which takes into account all the features simultaneously in accordance with their respective variances. Extensive experiments dealing with several hours of video sequences in real-world scenarios have been conducted, showing a very promising performance.
Year
DOI
Venue
2005
10.1007/11677482_21
MLMI
Keywords
Field
DocType
scene understanding application,video surveillance,segmented view,foreground regions extraction,characteristic feature,object localization,camera view,template-based technique,real-time object tracking,object tracking task,object appearance,video sequence,object tracking
Voxel,Discretization,Computer vision,BitTorrent tracker,Pattern recognition,Computer science,Robustness (computer science),Video tracking,Artificial intelligence
Conference
Volume
ISSN
ISBN
3869
0302-9743
3-540-32549-2
Citations 
PageRank 
References 
21
1.19
7
Authors
2
Name
Order
Citations
PageRank
José Luis Landabaso11017.83
Montse Pardàs234335.03