This paper deals with automatically segmenting a person from challenging videos using a pose detector. A state of the art pose detector is used to detect the pose of a person from a frame in the video sequence. The pose is used to extract color and optical flow features to train a conditional random field to provide segmentation on multiple frames. Location from the pose is used to refine the results. No additional training data is required by the method. We also show how the pose results can be improved by our model.
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