Detecting and tracking bottoms and faces of the Crested Black Macaque in the wild

Chiverton, J., Micheletta, J. and Waller, B. ORCID: 0000-0001-6303-7458, 2015. Detecting and tracking bottoms and faces of the Crested Black Macaque in the wild. In: T. Amaral, S. Matthews, T. Plötz, S. McKenna and R. Fisher, eds., Proceedings of the Workshop on Machine Vision of Animals and their Behaviour (MVAB 2015). British Machine Vision Association Press, 9.1 - 9.8. ISBN 1901725537

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Abstract

Monkeys are important to many areas of science and ecology. The study of monkeys and their welfare are important components requiring complex observational studies. This work is therefore concerned with the development of computer vision techniques for the purposes of detecting and tracking monkeys with the ultimate aim to help in such studies. Monkeys are complex creatures for the purposes of tracking because of complex deformations. This complexity is further compounded by an in the wild setting where forest conditions result in frequent occlusions and changes in lighting. Despite these complexities monkeys present some interesting features that can make detection and tracking possible: their bottoms and faces. A system is thus described consisting of detectors trained to detect faces and bottoms of monkeys which are used within a tracking framework to initialise a system of tracklet construction. Steps are also described to enable disparate but coincident tracklets to be merged thus enabling longer run analysis of individual monkey movements. Experiments are performed using image data taken from video footage of Crested Black Macaques in natural forest surroundings. Results demonstrate relatively successful detection of monkey bottoms where the correspondence analysis and tracking process helps to reduce false positives.

Item Type: Chapter in book
Description: Paper presented at the Workshop on Machine Vision of Animals and their Behaviour (MVAB 2015), Swansea, 7-10 September 2015.
Creators: Chiverton, J., Micheletta, J. and Waller, B.
Publisher: British Machine Vision Association Press
Date: September 2015
ISBN: 1901725537
Identifiers:
NumberType
10.5244/c.29.mvab.9DOI
1385562Other
Divisions: Schools > School of Social Sciences
Record created by: Linda Sullivan
Date Added: 09 Nov 2020 10:47
Last Modified: 09 Nov 2020 10:48
URI: http://irep.ntu.ac.uk/id/eprint/41564

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