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Summary: (To appear. ACM Computing Surveys.)
Human Activity Analysis: A Review
J. K. Aggarwal1
and M. S. Ryoo1,2
1
The University of Texas at Austin
2
Electronics and Telecommunications Research Institute
Human activity recognition is an important area of computer vision research. Its applications
include surveillance systems, patient monitoring systems, and a variety of systems that involve
interactions between persons and electronic devices such as human-computer interfaces. Most
of these applications require an automated recognition of high-level activities, composed of mul-
tiple simple (or atomic) actions of persons. This paper provides a detailed overview of various
state-of-the-art research papers on human activity recognition. We discuss both the methodolo-
gies developed for simple human actions and those for high-level activities. An approach-based
taxonomy is chosen, comparing the advantages and limitations of each approach.
Recognition methodologies for an analysis of simple actions of a single person are first pre-
sented in the paper. Space-time volume approaches and sequential approaches that represent
and recognize activities directly from input images are discussed. Next, hierarchical recognition
methodologies for high-level activities are presented and compared. Statistical approaches, syntac-
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