NDLI: Use of convolutional neural networks to automate the detection of wildlife from remote cameras

Content Provider	IEEE Xplore Digital Library
Author	Maiti, R. Yi Hou Cassady St. Clair, C. Hong Zhang
Copyright Year	2015
Description	Author affiliation: Nat. Univ. of Defense Technol., Changsha, China (Yi Hou) \|\| Dept. of Biol. Sci., Univ. of Alberta, Edmonton, AB, Canada (Cassady St. Clair, C.) \|\| Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada (Maiti, R.; Hong Zhang)
Abstract	Determining the abundance, distribution, and habitat associations of wildlife species is important for understanding their ecology, behavior and conservation. For mobile, rare, and wide-ranging species, biologists often obtain this information from remote cameras and time-lapse photography. The captured images are then visually inspected to identify those that contain useful information. Due to the large number of images to be processed, the task of visual inspection is painstaking and tedious. In this paper, we describe preliminary results of an automated screening system that is intended to alleviate this problem. Specifically, we study the problem of detecting grizzly bears (Ursus acrtos) in still images, using a convolutional neural network (CNN). Given each image, we first use the Maximally Stable Extremal Regions (MSER) to segment sub-regions that potentially contain a bear and then apply a pre-trained convolutional neural network as the classifier to determine if a bear is present in a sub-region. Experimental results from a real-world dataset demonstrate that our system is able to eliminate over 90% of the images from human inspection while recalling over 60% of the positive images that contain a bear, at a rate of approximately one minute per image.
Starting Page	42
Ending Page	47
File Size	5209249
Page Count	6
File Format	PDF
ISBN	9781467373371
ISSN	23268239
e-ISBN	9781467373388
DOI	10.1109/ICCIS.2015.7274594
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-15
Publisher Place	Cambodia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proposals Feature extraction Visualization Cameras Wildlife Semantics Random access memory
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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