Evrişimsel Sinir Aǧi Öznitelikleri ile Kişiyi Yeniden Tanima

Translated title of the contribution: Convolutional neural network-based representation for person re-identification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

In this paper, using a general convolutional neural network (CNN) model, which was developed for object recognition, a successful system has been introduced for the person re-identification problem. To use this CNN model for the person re-identification problem properly, it is individually fine-tuned using different body parts of person images. For feature extraction, we used the seventh layer of the CNN model, which was re-trained with the available datasets. Then, we used cosine similarity metric to calculate the similarity between extracted features. CUHK03 and Market-1501 datasets were used as the training sets and the proposed method has been tested on VIPeR dataset. Superior results have been obtained with the proposed method, compared to the state-of-the-art methods in the field.

Translated title of the contributionConvolutional neural network-based representation for person re-identification
Original languageTurkish
Title of host publication2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages945-948
Number of pages4
ISBN (Electronic)9781509016792
DOIs
Publication statusPublished - 20 Jun 2016
Event24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey
Duration: 16 May 201619 May 2016

Publication series

Name2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference24th Signal Processing and Communication Application Conference, SIU 2016
Country/TerritoryTurkey
CityZonguldak
Period16/05/1619/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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