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Studies on Various Type of Human Detection Algorithms for Multiple and Occluded Persons in Static Images

Journal of Applied Information Science

Volume 5 Issue 2

Published: 2017
Author(s) Name: M. Shanmugasundaram, N. Shanmuga Vadivu | Author(s) Affiliation: Dept. of CS, College of Comp. Scie. & Information Systems, JAZAN Univer, Kingdom of Saudi Arabia.
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Detecting and tracking human in still or video images provides a promising technology development and solution to many real world problems. Moreover, detecting human may be the first step to put forward the next logical steps for many applications. But, it is a challenging task due pose, dresses, color and occlusion. This paper proposes a study of human detection in static images in different view. In the literature, numerous works had been proposed to detect a single human in an image. So, the survey has been conducted for detection of multiple humans without occlusion, detection of multiple human with occlusion and human detection in fused image. Due to the difficulties found during the process of human detection such as occlusion and shadow, people in group, main focus has been given to multiple-human detection.

Keywords: Human detection, Pose, Occlusion, fusion, Machine learning, Object detection, Feature extraction.

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