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Detecting and tracking bottoms and faces of the crested black macaque in the wild

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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 for
est 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.
Original languageEnglish
Title of host publicationProceedings of the Machine Vision of Animals and their Behaviour Workshop (MVAB) 2015
EditorsXianghua Xie, Mark Jones, Gary Tam
PublisherBritish Machine Vision Association
Pages1-8
ISBN (Electronic)1-901725-53-7
DOIs
Publication statusPublished - 10 Sep 2015
EventMachine Vision of Animals and their Behaviour Workshop (MVAB 2015) - Swansea, United Kingdom
Duration: 7 Sep 201510 Sep 2015

Workshop

WorkshopMachine Vision of Animals and their Behaviour Workshop (MVAB 2015)
CountryUnited Kingdom
CitySwansea
Period7/09/1510/09/15

Documents

  • jcjmbw_mvab2015_rev2

    Accepted author manuscript (Post-print), 8 MB, PDF document

    Licence: Unspecified

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ID: 3179378