Application of Selective Search to Pose estimation
نویسنده
چکیده
This paper will apply the generic objectness measure to sample windows from a given image and then feed them through a human pose estimation pipeline. The Objectness step will provide windows in the BUFFY and PARSE datasets and some of them will contain people. This approach would be better than a scanning window technique in terms of computational speed as the filter convolution step of the pose estimation algorithm can be computed in selective regions of the input image. We discuss the results obtained using the above described pipeline and another baseline over the BUFFY and PARSE datasets.
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