Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering

Dominik Pieczyński (Poznań University of Technology, Poland)

Marek Kraft (Poznań University of Technology, Poland)

Michał Fularz (Poznań University of Technology, Poland)

Abstract: In this paper, a method for improving the quality of person re-identification results is presented. The method is based on the assumption, that including segmentation information into re-identi_cation pipeline discards the automated detections that are of poor quality due to occlusions, misplaced regions of interest (ROI), multiple persons found within a single ROI, etc. using a simple segment number, bounding box fill rate and aspect ratio check. Assuming that a joint detector-segmented approach is used, the additional cost associated with the use of the proposed approach is very low.

Keywords: computer vision, deep learning, person re-identification, segmentation

Categories: I.2.1, I.2.10, I.4.9,, I.5.4