DMCA
Human Activity Analysis: A Review
| Venue: | TO APPEAR. ACM COMPUTING SURVEYS. |
| Citations: | 214 - 6 self |
BibTeX
@MISC{Aggarwal_humanactivity,
author = {J. K. Aggarwal and M. S. Ryoo},
title = {Human Activity Analysis: A Review},
year = {}
}
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Abstract
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 multiple 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 methodologies 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 presented 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, syntactic approaches, and description-based approaches for hierarchical recognition are discussed in the paper. In addition, we further discuss the papers on the recognition of human-object interactions and group activities. Public datasets designed for the evaluation of the recognition methodologies are illustrated in our paper as well, comparing the methodologies’ performances. This review will provide the impetus for future research in more productive areas.
Keyphrases
human activity analysis high-level activity recognition methodology human activity recognition syntactic approach multiple simple single person description-based approach human-object interaction statistical approach important area patient monitoring system hierarchical recognition productive area sequential approach human-computer interface simple action automated recognition public datasets space-time volume approach group activity detailed overview electronic device methodology performance input image various state-of-the-art research paper surveillance system approach-based taxonomy hierarchical recognition methodology simple human action future research computer vision research
