@inproceedings{55f79759b8744e278d0f6fc60cdba5af,
title = "Recognition of human group activity for video analytics",
abstract = "Human activity recognition is an important and challenging task for video content analysis and understanding. Individual activity recognition has been well studied recently. However, recognizing the activities of human group with more than three people having complex interactions is still a formidable challenge. In this paper, a novel human group activity recognition method is proposed to deal with complex situation where there are multiple sub-groups. To characterize the inherent interactions of intra-subgroups and inter-subgroups with the varying number of participants, this paper proposes three types of group-activity descriptor using motion trajectory and appearance information of people. Experimental results on a public human group activity dataset demonstrate effectiveness of the proposed method.",
keywords = "Activity recognition, Human group activity, Video analytics",
author = "Jaeyong Ju and Cheoljong Yang and Sebastian Scherer and Hanseok Ko",
note = "Funding Information: This research was supported by BK21 PLUS Program. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 16th Pacific-Rim Conference on Multimedia, PCM 2015 ; Conference date: 16-09-2015 Through 18-09-2015",
year = "2015",
doi = "10.1007/978-3-319-24078-7_16",
language = "English",
isbn = "9783319240770",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "161--169",
editor = "Yo-Sung Ho and Ro, {Yong Man} and Junmo Kim and Fei Wu and Jitao Sang",
booktitle = "Advances in Multimedia Information Processing – PCM 2015 - 16th Pacific-Rim Conference on Multimedia, Proceedings",
}