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

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 re...

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Bibliographic Details
Published in:Journal of Universal Computer Science
Main Authors: Dominik Pieczyński, Marek Kraft, Michał Fularz
Format: Article
Language:English
Published: Graz University of Technology 2019-06-01
Subjects:
person re-identification
computer vision
deep le
Online Access:https://lib.jucs.org/article/22615/download/pdf/
Description
Summary: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.
ISSN:0948-6968

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