A Fast Non-Overlapping Multi-Camera People Re-Identification Algorithm and Tracking Based on Visual Channel Model

Chi-Chia SUN  Ming-Hwa SHEU  Jui-Yang CHI  Yan-Kai HUANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D    No.7    pp.1342-1348
Publication Date: 2019/07/01
Publicized: 2019/04/18
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDP7348
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
multi-camera,  people re-identification,  visual channel model,  embedded,  

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In this paper, a nonoverlapping multi-camera and people re-identification algorithm is proposed. It applies inflated major color features for re-identification to reduce computation time. The inflated major color features can dramatically improve efficiency while retaining high accuracy of object re-identification. The proposed method is evaluated over a wide range of experimental databases. The accuracy attains upwards of 40.7% in Rank 1 and 84% in Rank 10 on average, while it obtains three to 15 times faster than algorithms reported in the literature. The proposed algorithm has been implemented on a SOC-FPGA platform to reach 50 FPS with 1280×720 HD resolution and 25 FPS with 1920×1080 FHD resolution for real-time processing. The results show a performance improvement and reduction in computation complexity, which is especially ideal for embedded platform.

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