Adapting simulated behaviors for new characters
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Synthesis of complex dynamic character motion from simple animations
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Computing the Physical Parameters of Rigid-Body Motion from Video
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Computer Graphics with OpenGL
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In this paper, we propose a novel two-level regression method for computing body mass distribution from a database of X-ray images, without scanning the new subject. Our approach first selects a suitable sample from the image database by minimizing a distance function based on the relationships between the new subject's body measurements and those of sample subjects. The X-ray image of the new subject is then predicted from the sample image using a feature-based transformation. Body mass distribution is computed directly from the predicted X-ray image. Our results surpass the accuracy of commonly used mass distribution regression methods in biomechanics literatures. In addition, by not scanning the new subject, we avoid all the radiation and cost involved in X-ray absorptiometry.