Integral and Indexing based Feature Extraction Method for Human Detection and Tracking

Authors(2) :-Jaykumar Limbasiya, Hitul Marvaniya

The detection and tracking of the human being in Video surveillance is a vibrant research topic in computer vision. It replaces old traditional method of monitoring camera feed by the human being by automatically detect and tracking along with the understanding of human behavior. Surveillance systems must be self-directed to improve the performance and eliminate such operator errors. Ideally, an automated surveillance system should only require the objectives of an application, in which there are real-time understanding of activities. Human detection includes detecting humans in each frame of video. Either each tracking method requires an object detection mechanism in every frame or when the object first appears in the video. Human tracking is the method of detecting human over time on the camera feed. The fast and efficient camera, high-quality videos, low priced camera and increasing need for the automatic system for detection and tracking will create interest in human tracking algorithms.

Authors and Affiliations

Jaykumar Limbasiya
PG Student, Information Technology Department, V.V.P. Engineering College, Rajkot, Gujarat, India
Hitul Marvaniya
Assistant Professor, Information Technology Department, V.V.P. Engineering College, Rajkot Gujarat, India

Human Tracking, Video Surveillance, Detection, Object Detection and Tracking, Feature Extraction, keypoints detection, Point tracking

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 351-355
Manuscript Number : CSEIT1726111
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Jaykumar Limbasiya, Hitul Marvaniya, "Integral and Indexing based Feature Extraction Method for Human Detection and Tracking", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.351-355, November-December-2017.
Journal URL : http://ijsrcseit.com/CSEIT1726111

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