Detecting and Tracking Bottoms and Faces of the Crested Black Macaque in the Wild

John Chiverton, Jerome Micheletta and Bridget Waller

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.

Session

Workshop: Machine Vision of Animals and their Behaviour (MVAB 2015)

Files

Paper (PDF, 8M)

DOI

10.5244/C.29.MVAB.9
https://dx.doi.org/10.5244/C.29.MVAB.9

Citation

Bibtex

@inproceedings{MVAB2015_9,
	title={Detecting and Tracking Bottoms and Faces of the Crested Black Macaque in the Wild},
	author={John Chiverton and Jerome Micheletta and Bridget Waller},
	year={2015},
	month={September},
	pages={9.1-9.8},
	articleno={9},
	numpages={8},
	booktitle={Proceedings of the Machine Vision of Animals and their Behaviour (MVAB)},
	publisher={BMVA Press},
	editor={T. Amaral, S. Matthews, T. Plötz, S. McKenna, and R. Fisher},
	doi={10.5244/C.29.MVAB.9},
	isbn={1-901725-57-X},
	url={https://dx.doi.org/10.5244/C.29.MVAB.9}
}