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Person re‐identification with local descriptors across multicameras
Author(s) -
Huang Qiao,
Yang Jie
Publication year - 2013
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1556
Subject(s) - computer science , robustness (evolution) , artificial intelligence , computer vision , identification (biology) , task (project management) , motion (physics) , human motion , support vector machine , pattern recognition (psychology) , biochemistry , chemistry , botany , management , biology , economics , gene
ABSTRACT Tracking the same person across multiple cameras is an important task in human motion analysis systems. It is also desirable to re‐identify the individuals who have been previously seen with a single camera. This paper addresses this problem by the re‐identification of the same individual in two different datasets, which are both challenging situations from human motion analysis systems. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient bag‐of‐features approach for image presentation. In this way, robustness against low resolution, occlusion, and pose, viewpoint and illumination changes is achieved in a very fast way. We obtain promising results from the evaluation with situations where a number of individuals vary continuously from a multicamera system. Copyright © 2013 John Wiley & Sons, Ltd.