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Hidden Markov Model Classifier for the Adaptive Particle Swarm Optimization Read chapter Read first chapter

2018 | OriginalPaper | Chapter

25. Towards a Novel Reidentification Method Using Metaheuristics

Authors : Tarik Ljouad, Aouatif Amine, Ayoub Al-Hamadi, Mohammed Rziza

Published in: Recent Developments in Metaheuristics

Publisher: Springer International Publishing

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Abstract

Tracking multiple moving objects in a video sequence can be formulated as a profile matching problem. Reidentifying a profile within a crowd is done by a matching process between the tracked person and the different moving individuals within the same frame. In that context, the feature matching task can be approximated to a search for the profile that maximizes a considered similarity measure. In this work, we introduce a novel Modified Cuckoo Search (MCS) based reidentification algorithm. A complex descriptor representing each moving person is built from different low level visual features such as the color and the texture components. We make use of a database that involves all previously detected descriptors, forming therefore a discrete search space where the sought solution is a descriptor and its quality is represented by its similarity to the query profile. The approach is evaluated within a multiple object tracking scenario, and a validation process using the normalized cross correlation method to accept or reject the obtained reidentification results is included. The experimental results show promising performances in terms of computation cost as well as reidentification rate.

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previous chapter Surrogate-Assisted Multiobjective Evolutionary Algorithm for Fuzzy Job Shop Problems
next chapter Facing the Feature Selection Problem with a Binary PSO-GSA Approach
Footnotes
1
Example of reidentification open-source project: https://​github.​com/​Robert0812/​saliencereid introduced by Zhao et al. [26].
 
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Metadata
Title
Towards a Novel Reidentification Method Using Metaheuristics
Authors
Tarik Ljouad
Aouatif Amine
Ayoub Al-Hamadi
Mohammed Rziza
Copyright Year
2018
Book
Recent Developments in Metaheuristics

Print ISBN: 978-3-319-58252-8

Electronic ISBN: 978-3-319-58253-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-58253-5_25