TY - GEN
T1 - Evrişimsel Sinir Aǧi Öznitelikleri ile Kişiyi Yeniden Tanima
AU - Ulu, Alper
AU - Ekenel, Hazim Kemal
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/20
Y1 - 2016/6/20
N2 - 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.
AB - 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.
KW - convolutional neural network
KW - cosine similarity
KW - person re-identification
UR - http://www.scopus.com/inward/record.url?scp=84982806149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982806149&partnerID=8YFLogxK
U2 - 10.1109/SIU.2016.7495897
DO - 10.1109/SIU.2016.7495897
M3 - Conference contribution
AN - SCOPUS:84982806149
T3 - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
SP - 945
EP - 948
BT - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th Signal Processing and Communication Application Conference, SIU 2016
Y2 - 16 May 2016 through 19 May 2016
ER -