3D Human model adaptation by frame selection and shape-texture optimization
نویسندگان
چکیده
We present a novel approach for 3D human body shape model adaptation to a sequence of multi-view images, given an initial shape model and initial pose sequence. In a first step, the most informative frames are determined by optimization of an objective function that maximizes a shape–texture likelihood function and a pose diversity criterion (i.e. the model surface area that lies close to the occluding contours), in the selected frames. Thereafter, a batch-mode optimization is performed of the underlying shapeand pose-parameters, by means of an objective function that includes both contour and texture cues over the selected multi-view frames. Using above approach, we implement automatic pose and shape estimation using a three-step procedure: first, we recover initial poses over a sequence using an initial (generic) body model. Both model and poses then serve as input to the above mentioned adaptation process. Finally, a more accurate pose recovery is obtained by means of the adapted model. We demonstrate the effectiveness of our frame selection, model adaptation and integrated pose and shape recovery procedure in experiments using both challenging outdoor data and the HumanEva data set. 2011 Elsevier Inc. All rights reserved.
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عنوان ژورنال:
- Computer Vision and Image Understanding
دوره 115 شماره
صفحات -
تاریخ انتشار 2011