We propose an approach to the task of automatic pose initialization of swimmers in videos. Thus, our goal is to detect a swimmer inside a target video and assign an estimated position to her/his body parts. We first apply a non-skin-color filter to reduce the search spate inside each target frame. We then match previously devised template sequences of Gaussian feature descriptors against sequences of feature vectors which are computed within the remaining image regions. Finally, relative average joint positions from annotated images featuring the key pose are assigned to the detection result and three-dimensional joint positions are estimated. We present detection results for test videos of three different swim strokes and examine the performance of four types of feature descriptors.
展开▼
