Two-Stage filtering scheme for sparse representation based interest point matching for person Re-identification

Mohamed Ibn Khedher, Mounim A. El Yacoubi

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The objective of this paper is to study Interest Points (IP) filtering in video-based human re-identification tasks. The problem is that having a large number of IPs to describe person, Re-identification grows into a much time consuming task and IPs become redundant. In this context, we propose a Two-Stage filtering step. The first stage reduces the number of IP to be matched and the second ignores weak matched IPs participating in the re-identification decision. The proposed approach is based on the supervision of SVM, learned on training dataset. Our approach is evaluated on the dataset PRID-2011 and results show that it is fast and compare favorably with the state of the art.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages345-356
Number of pages12
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9386
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Filtering
  • Interest point
  • Person re-identification
  • SVM
  • Sparse representation

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