TY - GEN
T1 - Historical image annotation by exploring the tag relevance
AU - Zhang, Junjie
AU - Zhang, Jian
AU - Wu, Qi
AU - Wu, Qiang
AU - Xu, Jinsong
AU - Lu, Jianfeng
AU - Phua, Robin
AU - Curr, Kate
AU - Tang, Zhenmin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/12/13
Y1 - 2018/12/13
N2 - Historical images usually contain enormous historical research value and are highly related to the history objects, events and background stories etc. Therefore, annotating these images always requires selecting tags within a large set. In this paper, we propose to annotate historical images by exploring the tag relevance. We measure the tag relevance from three different perspectives, including its visual relevance, its dependencies with other tags and its relationship with location based meta-data. By using tag relevance as guidance, we generate three tag sub-sets and use them to fulfill the annotation. Experimental results on the benchmark dataset indicate the significance of exploring the tag relevance by comparing with the baseline experiments.
AB - Historical images usually contain enormous historical research value and are highly related to the history objects, events and background stories etc. Therefore, annotating these images always requires selecting tags within a large set. In this paper, we propose to annotate historical images by exploring the tag relevance. We measure the tag relevance from three different perspectives, including its visual relevance, its dependencies with other tags and its relationship with location based meta-data. By using tag relevance as guidance, we generate three tag sub-sets and use them to fulfill the annotation. Experimental results on the benchmark dataset indicate the significance of exploring the tag relevance by comparing with the baseline experiments.
KW - Annotation
KW - Historical images
KW - Tag relevance
UR - http://www.scopus.com/inward/record.url?scp=85060543732&partnerID=8YFLogxK
U2 - 10.1109/ACPR.2017.144
DO - 10.1109/ACPR.2017.144
M3 - Conference Proceeding
AN - SCOPUS:85060543732
T3 - Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
SP - 646
EP - 651
BT - Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th Asian Conference on Pattern Recognition, ACPR 2017
Y2 - 26 November 2017 through 29 November 2017
ER -