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arXiv · 2501.11030

Tracking Mouse from Incomplete Body-Part Observations and Deep-Learned Deformable-Mouse Model Motion-Track Constraint for Behavior Analysis

Olaf Hellwich·Niek Andresen·Katharina Hohlbaum·Marcus N. Boon·Monika Kwiatkowski·Simon Matern·Patrik Reiske·Henning Sprekeler·Christa ThöneReineke·Lars Lewejohann·Huma Ghani Zada·Michael Brück·Soledad Traverso
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Abstract

Tracking mouse body parts in video is often incomplete due to occlusions such that - e.g. - subsequent action and behavior analysis is impeded. In this conceptual work, videos from several perspectives are integrated via global exterior camera orientation; body part positions are estimated by 3D triangulation and bundle adjustment. Consistency of overall 3D track reconstruction is achieved by introduction of a 3D mouse model, deep-learned body part movements, and global motion-track smoothness constraint. The resulting 3D body and body part track estimates are substantially more complete than the original single-frame-based body part detection, therefore, allowing improved animal behavior analysis.

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Olaf Hellwich, Niek Andresen, Katharina Hohlbaum, Marcus N. Boon, Monika Kwiatkowski, Simon Matern, Patrik Reiske, Henning Sprekeler, Christa ThöneReineke, Lars Lewejohann, Huma Ghani Zada, Michael Brück, Soledad Traverso. 2025-01-19. Tracking Mouse from Incomplete Body-Part Observations and Deep-Learned Deformable-Mouse Model Motion-Track Constraint for Behavior Analysis. https://arxiv.org/abs/2501.11030

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