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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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:
Online Access:https://lib.jucs.org/article/22615/download/pdf/
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author Dominik Pieczyński
Marek Kraft
Michał Fularz
author_facet Dominik Pieczyński
Marek Kraft
Michał Fularz
author_sort Dominik Pieczyński
collection DOAJ
container_title Journal of Universal Computer Science
description 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.
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spelling doaj-art-bc341827eab148ae8eae368f514b2a7a2025-08-19T21:09:57ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682019-06-0125661162610.3217/jucs-025-06-061122615Improving Person Re-identification by Segmentation-Based Detection Bounding Box FilteringDominik Pieczyński0Marek Kraft1Michał Fularz2Poznań University of TechnologyPoznań University of TechnologyPoznań University of TechnologyIn 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.https://lib.jucs.org/article/22615/download/pdf/person re-identificationcomputer visiondeep le
spellingShingle Dominik Pieczyński
Marek Kraft
Michał Fularz
Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
person re-identification
computer vision
deep le
title Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
title_full Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
title_fullStr Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
title_full_unstemmed Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
title_short Improving Person Re-identification by Segmentation-Based Detection Bounding Box Filtering
title_sort improving person re identification by segmentation based detection bounding box filtering
topic person re-identification
computer vision
deep le
url https://lib.jucs.org/article/22615/download/pdf/
work_keys_str_mv AT dominikpieczynski improvingpersonreidentificationbysegmentationbaseddetectionboundingboxfiltering
AT marekkraft improvingpersonreidentificationbysegmentationbaseddetectionboundingboxfiltering
AT michałfularz improvingpersonreidentificationbysegmentationbaseddetectionboundingboxfiltering