TY - GEN
T1 - Human interaction recognition in YouTube videos
AU - Cho, Sunyoung
AU - Lim, Seongho
AU - Byun, Hyeran
AU - Park, Haejin
AU - Kwak, Sooyeong
PY - 2011
Y1 - 2011
N2 - This paper introduces the use of annotation tags for human activity recognition in video. Recent methods in human activity recognition use more complex and realistic datasets obtained from TV shows or movies, which makes it difficult to obtain the high recognition accuracies. We improve the recognition accuracies using annotation tags of the video. Tags tend to be related to video contents, and human activity videos frequently contain tags relevant to their activities. We first collect a human activity dataset containing tags from YouTube. Under this dataset, we automatically discover relevant tags and their correlation with human activities. We finally develop a framework using visual content and tags for activity recognition. We show that our approach can improve recognition accuracies compared with other approaches that only use visual content.
AB - This paper introduces the use of annotation tags for human activity recognition in video. Recent methods in human activity recognition use more complex and realistic datasets obtained from TV shows or movies, which makes it difficult to obtain the high recognition accuracies. We improve the recognition accuracies using annotation tags of the video. Tags tend to be related to video contents, and human activity videos frequently contain tags relevant to their activities. We first collect a human activity dataset containing tags from YouTube. Under this dataset, we automatically discover relevant tags and their correlation with human activities. We finally develop a framework using visual content and tags for activity recognition. We show that our approach can improve recognition accuracies compared with other approaches that only use visual content.
UR - http://www.scopus.com/inward/record.url?scp=84860626870&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860626870&partnerID=8YFLogxK
U2 - 10.1109/ICICS.2011.6173540
DO - 10.1109/ICICS.2011.6173540
M3 - Conference contribution
AN - SCOPUS:84860626870
SN - 9781457700309
T3 - ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing
BT - ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing
T2 - 8th International Conference on Information, Communications and Signal Processing, ICICS 2011
Y2 - 13 December 2011 through 16 December 2011
ER -