CIARP 2014: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications pp 359-366 | Cite as
Person Re-Identification Based on Weighted Indexing Structures
Abstract
Surveillance cameras are present almost everywhere, indicating an increasing interest regarding people safety. The automation of surveillance systems is important to allow real time analysis of critical events, crime investigation and prevention. A crucial step in the surveillance systems is the person re-identification which aims at maintaining the identity of agents that pass through the monitored environment, despite the occurrence of significant gaps in time and space. Many approaches have been proposed to person re-identification. However, there are still problems to be solved, such as illumination changes, pose variation, occlusions, appearance modeling and the management of the large number of people being monitored. This work approaches the last problem with the employment of multiple indexing structures associated with a weighting strategy to maintain the scalability and improve the accuracy. Experimental results demonstrate that the proposed approach is able to improve results based only on a single indexing structure.
Keywords
Person re-identification weighting strategies visual dictionaries predominance filter inverted listsPreview
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