A Compilation of Methods and Datasets for Group and Crowd Action Recognition

A Compilation of Methods and Datasets for Group and Crowd Action Recognition

Luis Felipe Borja (Universidad Central del Ecuador, Quito, Ecuador), Jorge Azorin-Lopez (Department of Computer Technology, University of Alicante, Alicante, Spain) and Marcelo Saval-Calvo (Department of Computer Technology, University of Alicante, Alicante, Spain)
Copyright: © 2017 |Pages: 14
DOI: 10.4018/IJCVIP.2017070104
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Abstract

The human behaviour analysis has been a subject of study in various fields of science (e.g. sociology, psychology, computer science). Specifically, the automated understanding of the behaviour of both individuals and groups remains a very challenging problem from the sensor systems to artificial intelligence techniques. Being aware of the extent of the topic, the objective of this paper is to review the state of the art focusing on machine learning techniques and computer vision as sensor system to the artificial intelligence techniques. Moreover, a lack of review comparing the level of abstraction in terms of activities duration is found in the literature. In this paper, a review of the methods and techniques based on machine learning to classify group behaviour in sequence of images is presented. The review takes into account the different levels of understanding and the number of people in the group.
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2. Aspects Of Human Behavior Analysis

In this section, the main aspects of the human behavior analysis are explained. First, we will present the different levels of understanding and later the main datasets available for experimentation.

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