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Quadruped locomotion analysis using three-dimensional video

Abdul Jabbar, Khalid; Hansen, Mark F; Smith, Melvyn; Smith, Lyndon

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Authors

Khalid Abdul Jabbar

Mark Hansen Mark.Hansen@uwe.ac.uk
Professor of Machine Vision and Machine Learning

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine



Abstract

Abstract— To date, there has not been a single method
suitable for large-scale or regular-basis implementation to analyze the locomotion of quadruped animals. Existing methods are not sensitive enough for detecting minor deviations from healthy gaits. That is important because these minor deviations could develop into a severe painful lameness condition. We introduce a dynamic novel proxy for early stage lameness by analyzing the height movements from an overhead-view 3D video data. These movements are derived from key regions (e.g. spine, hook joints, and sacroiliac joint). The features to these key regions are automatically tracked using shape index and curvedness threshold from the 3D map. Our system is fully automated, covert and non-intrusive. This directly affects the accuracy of the analysis as we are able to observe the animals without spooking them. We believe that our proposed method could be used on other animals, i.e. predator quadrupeds where human presence is difficult.

Citation

Abdul Jabbar, K., Hansen, M. F., Smith, M., & Smith, L. (2016, October). Quadruped locomotion analysis using three-dimensional video. Paper presented at IEEE ICSAE Conference, Newcastle, UK

Presentation Conference Type Conference Paper (unpublished)
Conference Name IEEE ICSAE Conference
Conference Location Newcastle, UK
Start Date Oct 20, 2016
End Date Oct 21, 2016
Acceptance Date Aug 22, 2016
Publication Date Jan 9, 2017
Deposit Date Sep 15, 2016
Publicly Available Date Jan 24, 2017
Peer Reviewed Peer Reviewed
Keywords quadruped locomotion, lameness detection, 3D computer vision
Public URL https://uwe-repository.worktribe.com/output/900125
Publisher URL http://dx.doi.org/10.1109/ICSAE.2016.7810224
Additional Information Additional Information : (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Title of Conference or Conference Proceedings : IEEE ICSAE Conference

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