TY - GEN
T1 - Person Re-Identification in Movies/Dramas
AU - Im, Dong Hyuck
AU - Seo, Yong Seok
AU - Kim, Hyeonwoo
AU - Hwang, Eenjun
AU - Park, Jihyun
N1 - Funding Information:
ACKNOWLEDGMENT This research was supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Copyright Commission(KCC) in the Copyright Technology Research & Development Program 2020.
Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/10/21
Y1 - 2020/10/21
N2 - In this paper, we present a system for person re-identification in movies and dramas. Our person re-identification method simultaneously learns differences and commonalities between two pairs of images. Features are extracted using three images, and the relationship between the extracted features is constructed into two pairs of feature maps to learn. Our method significantly outperforms on a large data set (CUHK03), and our own re-identification dataset generated from video contents such as movies and dramas. We also show that the proposed model learned on our own data set can be applied to actor re-identification in video content.
AB - In this paper, we present a system for person re-identification in movies and dramas. Our person re-identification method simultaneously learns differences and commonalities between two pairs of images. Features are extracted using three images, and the relationship between the extracted features is constructed into two pairs of feature maps to learn. Our method significantly outperforms on a large data set (CUHK03), and our own re-identification dataset generated from video contents such as movies and dramas. We also show that the proposed model learned on our own data set can be applied to actor re-identification in video content.
KW - actor re-identification
KW - deep learning
KW - person re-identification
UR - http://www.scopus.com/inward/record.url?scp=85098945497&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098945497&partnerID=8YFLogxK
U2 - 10.1109/ICTC49870.2020.9289375
DO - 10.1109/ICTC49870.2020.9289375
M3 - Conference contribution
AN - SCOPUS:85098945497
T3 - International Conference on ICT Convergence
SP - 1596
EP - 1598
BT - ICTC 2020 - 11th International Conference on ICT Convergence
PB - IEEE Computer Society
T2 - 11th International Conference on Information and Communication Technology Convergence, ICTC 2020
Y2 - 21 October 2020 through 23 October 2020
ER -