Abstract
This paper presents a novel approach for behavior recognition from video data. A biologically inspired action representation is derived by applying a clustering algorithm to sequences of motion images. To obey the temporal context, we express behaviors as sequences of n-grams of basic actions. Novel video sequences are classified by comparing histograms of action n-grams to stored histograms of known behaviors. Experimental validation shows a high accuracy in behavior recognition. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Thurau, C., & Hlaváč, V. (2007). N-grams of action primitives for recognizing human behavior. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4673 LNCS, pp. 93–100). Springer Verlag. https://doi.org/10.1007/978-3-540-74272-2_12
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
