Superpixels Based Marker Tracking Vs. Hue Thresholding In Rodent Biomechanics Application
This work addresses the need for efficient marker tracking in rodent locomotion studies, but it is incremental as it compares existing segmentation techniques in a specific application.
The paper tackled the problem of automatic marker tracking for rodent biomechanics by comparing SLIC superpixels segmentation with hue thresholding, finding that the superpixels method was superior due to more reliable segmentation based on color and spatial information.
Examining locomotion has improved our basic understanding of motor control and aided in treating motor impairment. Mice and rats are premier models of human disease and increasingly the model systems of choice for basic neuroscience. High frame rates (250 Hz) are needed to quantify the kinematics of these running rodents. Manual tracking, especially for multiple markers, becomes time-consuming and impossible for large sample sizes. Therefore, the need for automatic segmentation of these markers has grown in recent years. We propose two methods to segment and track these markers: first, using SLIC superpixels segmentation with a tracker based on position, speed, shape, and color information of the segmented region in the previous frame; second, using a thresholding on hue channel following up with the same tracker. The comparison showed that the SLIC superpixels method was superior because the segmentation was more reliable and based on both color and spatial information.