Fig. 4
Tracking evaluation of DAMM. (A,B) Compilation of single-animal and multi-animal tracking evaluation datasets. Each dataset features videos with a mean duration of 45 s, in which the location and unique identification of every mouse are annotated throughout all frames. (C,D) DAMM is employed as the detection module within the Simple Online Real-time Tracking (SORT) algorithm to track mice in videos. The evaluation showcases (C) single-object and (D) multi-object tracking accuracy (IOU > .50) of DAMM for both zero-shot and 20-shot scenarios across all tracking datasets. (E) Comparison strategy and performance of DAMM with an existing keypoint-based-estimation mouse tracking method: the DLC SuperAnimal-TopViewMouse model. This model outputs keypoint predictions for top-view singly-housed mice. (F) Presented is a zero-shot tracking comparison on a subset of our previously introduced datasets which feature top-view singly-housed mice.
