Human layout estimation using structured output learning
In this thesis, we investigate the problem of human layout estimation in unconstrained still images. This involves predicting the spatial configuration of body parts.
We start our investigation with pictorial structure models and propose an efficient method of model fitting using skin regions. To detect the skin, we learn a colour model locally from the image by detecting the facial region. The resulting skin detections are also used for hand localisation.
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(Dissemination version, pdf, 46.1MB)
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- University of Oxford
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- Mittal, A
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