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Person Re-Identification by Semantic Region Representation and Topology Constraint
2018
IEEE transactions on circuits and systems for video technology (Print)
Person re-identification is a popular research topic which aims at matching the specific person in a multi-camera network automatically. Feature representation and metric learning are two important issues for person re-identification. In this paper, we propose a novel person re-identification method, which consists of a reliable representation called Semantic Region Representation (SRR), and an effective metric learning with Mapping Space Topology Constraint (MSTC). The SRR integrates semantic
doi:10.1109/tcsvt.2018.2866260
fatcat:xax4f32cvbbgjk5oggpu4d6l6q