Title
Branch And Bound Global Optima Search For Tracking A Single Object In A Network Of Non-Overlapping Cameras
Abstract
The paper presents a novel approach for single object tracking across non-overlapping camera views, which searches for the optimal association of single view trajectories. We map the tracking problem to a tree structure and introduce a branch and bound approach to efficiently explore the search space. We use an optimization criterion based solely on the geometric cues coming from the calibration of the network. The cost function is defined as to enforce consistency of geometrical and kinematic properties over the whole trajectory path. We show how the information content of the geometric properties of the network brings a substantial contribution to solve the association problem. Experiments in a set-up of four cameras using both synthetic and real trajectories validate the advantages of the approach both in terms of performance and information content of the geometric cue.
Year
DOI
Venue
2011
10.1109/ICCVW.2011.6130470
2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCV WORKSHOPS)
Keywords
Field
DocType
cost function,noise,information content,tree structure,three dimensional,search space,image reconstruction,geometry,calibration,object tracking,trajectory,branch and bound
Iterative reconstruction,Computer vision,Branch and bound,Kinematics,Computer science,Video tracking,Artificial intelligence,Tree structure,Calibration,Trajectory
Conference
Volume
Issue
Citations 
2011
1
2
PageRank 
References 
Authors
0.36
14
3
Name
Order
Citations
PageRank
Cristina Picus1221.53
Roman P. Pflugfelder29511.36
Branislav Micusík316610.70