A vision based human - elepahant collision detection system
ICIIP '15 Proceedings of the 2015 Third International Conference on Image Information Processing (ICIIP)(2015)
Abstract
Elephant intrusion in areas with high human movement can prove lethal for both human beings and elephants. The proposed system seeks to identify elephants with the aid of a Video Camera. The suggested methodology was applied to zones having high intervention of human beings and elephants. Regions with higher human movements like roads were extracted from the initial video frames. This process is followed by detecting motion in the video frame. The objects in the area of motion are then identified as elephant or non-elephant with the help of PHOG features and Support Vector Machines (SVM) classifiers. A dataset constituting of images of elephants and other objects was used for training the proposed algorithm. An overall accuracy of 85.29% was attained when static images containing elephants and other objects were classified. The same approach for detection was applied to identify moving elephants in the video frames. The proposed system endeavors to prevent casualties that occur in areas having high human elephant interaction.
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Key words
Human Elephant Collision, PHOG, animal detection, particle filtering
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