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(To appear. ACM Computing Surveys.) Human Activity Analysis: A Review

Summary: (To appear. ACM Computing Surveys.)
Human Activity Analysis: A Review
J. K. Aggarwal1
and M. S. Ryoo1,2
The University of Texas at Austin
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-


Source: Aggarwal, J. K. - Department of Electrical and Computer Engineering, University of Texas at Austin
Argonne National Laboratory, Mathematics and Computer Science Division (MCS)


Collections: Computer Technologies and Information Sciences; Engineering; Mathematics