Comparing Accelerometry and Depth Sensing-Based Computer Vision for Canine Tail Wagging Interpretation
Authors: 
Devon Martin, Timothy Holder, Colt Nichols, Jeremy Park, David Roberts, Alper BozkurtAuthors Info & Claims
Devon Martin, Timothy Holder, Colt Nichols, Jeremy Park, David Roberts, Alper BozkurtAuthors Info & ClaimsArticle No.: 20, Pages 1 - 8
Abstract
This paper presents a preliminary effort to evaluate alternative sensing modalities for automated, high-resolution tracking of dog tail position and movement as a behavioral communication tool. We compare two different methods: (1) inertial measurement devices placed on dog outfits, and (2) remotely positioned cameras supported with custom vision-based tail wag detection algorithms. The small size and non-invasiveness of the inertial sensors and the non-contact and remote nature of the camera system both promote subject comfort and continuous signal acquisition while not affecting the mechanics of dog tail movement. The preliminary findings support that the higher-resolution and continuous interpretations on the dog tail movements and positions can pave the way for assessing their emotional states and designing more appropriate training and play environments.
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- Comparing Accelerometry and Depth Sensing-Based Computer Vision for Canine Tail Wagging Interpretation
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Published In
December 2022
226 pages
ISBN:9781450398305
DOI:10.1145/3565995
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Association for Computing Machinery
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Published: 29 March 2023
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ACI'22
ACI'22: Ninth International Conference on Animal-Computer Interaction
December 5 - 8, 2022
Newcastle-upon-Tyne, United Kingdom
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