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Materials, Methods & Technologies, Volume 16, 2022

Sangam B. Neupane, Kazuhiko Sato, Bishnu P. Gautam
Pages: 282-295
Published: 16 Nov 2022
Views: 314
Downloads: 38
Abstract: Wildlife monitoring is critical for reducing poaching activities, tracking instinctive behavior, understanding the habitat, and recording the wild animal population. Biologists and scientists around the world are implementing various techniques to monitor wildlife. Observing animal behavior and supervising species over a large area necessitate extensive manual surveillance at a high cost. However, with technological advancement, data availability, and high computing power, techniques and methods used in monitoring wildlife are changing rapidly. In particular, the use of computer vision in identifying, classifying, and counting animals has been universally adopted in the scientific community because of its efficiency, repeatability, and high-accuracy rates. With the increasing use of computer vision techniques and IoT (Internet of Things) technologies, gaps, possibilities, and weaknesses are also being discovered. During our review, we discovered that many researchers are working in the field of deep learning and AI (Artificial Intelligence) technologies to improve the effectiveness and efficiency of wildlife monitoring systems. However, we realized that little research is being conducted on the preprocessing of image data captured by camera traps. In this paper, we compared and analyzed different computer vision techniques used in wildlife monitoring. We also evaluated various recent approaches for single and multi-object tracking from 148 different research papers and journals published between 2011 and 2022 on the specific topic of wildlife monitoring systems based on computer vision. Finally, we provide a detailed overview of future directions in designing and implementing computer vision techniques for wildlife monitoring and understanding.
Keywords: computer vision, wildlife conservation, camera traps, unmanned aerial vehicles (uav) tracking, infrared tracking
Cite this article: Sangam B. Neupane, Kazuhiko Sato, Bishnu P. Gautam. A LITERATURE REVIEW OF COMPUTER VISION TECHNIQUES IN WILDLIFE MONITORING. Journal of International Scientific Publications: Materials, Methods & Technologies 16, 282-295 (2022).
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