Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, an open-source pose estimation toolbox, and provide high-performance animal assembly and tracking—features required for multi-animal scenarios. Furthermore, we integrate the ability to predict an animal’s identity to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

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Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having extremely similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, a popular open source pose estimation toolbox, and provide high-performance animal assembly and tracking—features required for robust multi-animal scenarios. Furthermore, we integrate the ability to predict an animal’s identity directly to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

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The main muscle activities were observed during PP to perform powerful lower-limb extension. The most-skilled swimmer (S1) was the only 1 to solicit her muscles during GP to actively reach better streamlining. Important activation peaks during RP correspond to the limbs acting against water drag. Such differences in EMG strategies among an elite group highlight the importance of considering the muscle parameters used to effectively control the intensity of activation among the phases for a more efficient breaststroke kick.

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-L., Rouard, A. H. (2015). Breaststroke swimmers moderate internal work increases toward the highest stroke frequencies. Journal of Biomechanics, 48,

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