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
2019 IEICE transactions on information and systems  
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
more » ... 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. key words: multi-camera, people re-identification, visual channel model, embedded
doi:10.1587/transinf.2018edp7348 fatcat:slwv57jmazf2rai2wwdeco4doi