Group Action Recognition Using Space-Time Interest Points

Autor:	Qingdi Wei, Haibin Ling, Xiaoqin Zhang, Weiming Hu, Yu Kong
Rok vydání:	2009
Předmět:	Group (mathematics) business.industry Feature vector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Motion (physics) Task (project management) Group action Action (philosophy) Feature (machine learning) Computer vision Artificial intelligence business Cluster analysis Mathematics
Zdroj:	Advances in Visual Computing ISBN: 9783642105197 ISVC (2)
Popis:	Group action recognition is a challenging task in computer vision due to the large complexity induced by multiple motion patterns. This paper aims at analyzing group actions in video clips containing several activities. We combine the probability summation framework with the space-time (ST) interest points for this task. First, ST interest points are extracted from video clips to form the feature space. Then we use k-means for feature clustering and build a compact representation, which is then used for group action classification. The proposed approach has been applied to classification tasks including four classes: badminton, tennis, basketball, and soccer videos. The experimental results demonstrate the advantages of the proposed approach.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5454385970916b7df7095dd29ee10931 https://doi.org/10.1007/978-3-642-10520-3_72 Zobrazit plný text záznamu