Comparing Accelerometry and Depth Sensing-Based Computer Vision for Canine Tail Wagging Interpretation

Devon Martin, Timothy R. N. Holder, Colt Nichols, Jeremy Park, David L. Roberts, A. Bozkurt
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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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基于加速度测量和深度感知的计算机视觉在犬摇尾判读中的比较
本文提出了初步的努力,以评估替代传感模式的自动化,高分辨率跟踪狗尾巴的位置和运动作为一种行为交流工具。我们比较了两种不同的方法:(1)在狗身上放置惯性测量装置,(2)远程定位相机支持基于自定义视觉的尾巴摆动检测算法。惯性传感器的小尺寸和非侵入性以及相机系统的非接触式和远程特性都提高了受试者的舒适性和连续信号采集,同时不影响狗尾巴运动的力学。初步研究结果支持对狗尾巴运动和位置的高分辨率和连续解释可以为评估狗的情绪状态和设计更合适的训练和游戏环境铺平道路。
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