Spatial-temporal consistent labeling for multi-camera multi-object surveillance systems
Journal
Proceedings - IEEE International Symposium on Circuits and Systems
Pages
3530-3533
Date Issued
2008
Author(s)
Abstract
For an intelligent multi-camera multi-object surveillance system, object correspondence across time and space is important to many smart visual applications. In this paper, we propose a temporal and spatial consistent labeling algorithm for this demand. In the algorithm, an object corresponding database records the temporal and spatial consistency information for each segmented mask. With the database, the object-mask correlations are propagated through the propagation rules by analyzing mask splitting/merging conditions. In the spatial consistent labeling method, the homography warping and the earth mover's distance are adopted to match same objects across different views. The earth mover's distance solves the double matching problem, allows the algorithm to work normally under a small deviation of detected object locations, and makes pairing results have minimum global matching distances. The concept trusting-former-pairs-more is also adopted to avoid frequent pair switching if two objects are too close. The correct spatial labeling rate is about 89.25% in average. For online processing applications, the algorithm need not trace back to the past frames. The overall processing speed is about 10.24 frame per second (fps) with CIF size video running on a 2.8GHz general purpose CPU. ©2008 IEEE.
Event(s)
2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
Other Subjects
Boolean functions; Cameras; Computer networks; Labeling; Technical presentations; Video cameras; Earth Mover's distance; International symposium; Multi cameras; Multi objects; Security systems
Type
conference paper