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Title: A Computer Vision Framework for Detecting and Preventing Human-Elephant Collisions
Authors: Mittal A.
Dua I.
Shukla P.
Raman, Balasubramanian
Published in: Proceedings of 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Abstract: Human Elephant Collision (HEC) is a problem that is quite common across many parts of the world. There have been many incidents in the past where conflict between humans and elephants has caused serious damage and resulted in the loss of lives as well as property. The paper proposes a frame-work that relies on computer vision approaches for detecting and preventing HEC. The technique initially recognizes the areas of conflict where accidents are most likely to occur. This is followed by elephant detection system that identifies an elephant in the video frame. Two different algorithms to detect the presence of elephants having accuracies of 98.621% and 98.667% have been proposed in the paper. The position of the elephant once detected is tracked with respect to the area of conflict with a particle filter. A warning message is displayed as soon as the position of the elephant overlaps with the area of conflict. The results of the techniques that were applied on videos were discussed in the paper. © 2017 IEEE.
Citation: Proceedings of 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017, (2017), 2883- 2890
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Computer science
Detection system
Loss of life
Most likely
Video frame
Vision frameworks
Warning messages
Computer vision
ISBN: 9.78154E+12
Author Scopus IDs: 56152363000
Author Affiliations: Mittal, A., Graphic Era University, Dehradun, India
Dua, I., International Institute of Technology, Hyderabad, India
Shukla, P., University of California, Santa Barbara, United States
Raman, B., Indian Institute of Technology, Roorkee, India
Appears in Collections:Conference Publications [CS]

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