Identification Of Human Actions In Video Sequences

Abstract

The concept of an intelligent identification of human actions in videos is evolving as an active research area of computer vision and has covered a wide range of applications such as Ambient Assistive Living (AAL) [1], healthcare of elderly people [2], Intelligent Video surveillance systems [3], human-computer interfaces (HCI) [4] [5] , sports [6], event analysis, robotics [7], intrusion detection system [8], content-based video analysis [9], multimedia semantic annotation and indexing [10] etc. With the advent of technology and proliferating demand of society, automatic video sequence analysis based systems have become the need of the hour and their application in real life is helping to raise the standards of safety and security in society. The performance of the intelligent human action identification system greatly depends on the type of input fed to the systems, and features extracted from the input data. Feature designing plays an important role in understanding the actions in videos. However, various environmental conditions such as lighting conditions, cluttered background, partial or complete occlusion, crowded scenes, different viewpoint of the camera, size, shape, appearance and complexity of human actions, badly affect the process of discriminating feature. newline