TY - GEN
T1 - Who's the best charades player? Mining iconic movement of semantic concepts
AU - Hsieh, Yung Huan
AU - Hidayati, Shintami C.
AU - Cheng, Wen Huang
AU - Hu, Min-Chun
AU - Hua, Kai Lung
PY - 2014/2/7
Y1 - 2014/2/7
N2 - Charades is a guessing game with the idea for one player to act out a semantic concept (i.e. a word or phrase) for the other players to guess. An observation from playing charades is that people's cognition on the iconic movements associated with a semantic concept would be often inconsistent, and this fact has long been ignored in the multimedia research. Therefore, the novelty of this work is to propose an automation for mining the most representative videos for each semantic concept as its iconic movements from a large set of related videos containing various human actions. The discovered iconic movements can be further employed to benefit a broad range of tasks, such as human action recognition and retrieval. For our purpose, a new video benchmark is also presented and the experiments demonstrated our approach potential to human action based applications.
AB - Charades is a guessing game with the idea for one player to act out a semantic concept (i.e. a word or phrase) for the other players to guess. An observation from playing charades is that people's cognition on the iconic movements associated with a semantic concept would be often inconsistent, and this fact has long been ignored in the multimedia research. Therefore, the novelty of this work is to propose an automation for mining the most representative videos for each semantic concept as its iconic movements from a large set of related videos containing various human actions. The discovered iconic movements can be further employed to benefit a broad range of tasks, such as human action recognition and retrieval. For our purpose, a new video benchmark is also presented and the experiments demonstrated our approach potential to human action based applications.
UR - http://www.scopus.com/inward/record.url?scp=84893458282&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-04114-8_20
DO - 10.1007/978-3-319-04114-8_20
M3 - Conference contribution
AN - SCOPUS:84893458282
SN - 9783319041131
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 231
EP - 241
BT - MultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings
T2 - 20th Anniversary International Conference on MultiMedia Modeling, MMM 2014
Y2 - 6 January 2014 through 10 January 2014
ER -