Automatic Pose Initialization of Swimmers in Videos

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 space 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.