Adaptive Image-based Intersection Volume

Abstract : A method for image-based contact detection and modeling, with guaranteed precision on the intersection volume, is presented. Unlike previous image-based methods, our method optimizes a non-uniform ray sampling resolution and allows precise control of the volume error. By cumulatively projecting all mesh edges into a generalized 2D texture, we construct a novel data structure, the Error Bound Polynomial Image (EBPI), which allows efficient computation of the maximum volume error as a function of ray density. Based on a precision criterion, EBPI pixels are subdivided or clustered. The rays are then cast in the projection direction according to the non-uniform resolution. The EBPI data, combined with ray-surface intersection points and normals, is also used to detect transient edges at surface intersections. This allows us to model intersection volumes at arbitrary resolution, while avoiding the geometric computation of mesh intersections. Moreover, the ray casting acceleration data structures can be reused for the generation of high quality images.
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ACM Transactions on Graphics, Association for Computing Machinery, 2012, Proceedings of SIGGRAPH 2012, 31 (4), pp.Article No. 97. 〈10.1145/2185520.2185593〉
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Bin Wang, François Faure, Dinesh K. Pai. Adaptive Image-based Intersection Volume. ACM Transactions on Graphics, Association for Computing Machinery, 2012, Proceedings of SIGGRAPH 2012, 31 (4), pp.Article No. 97. 〈10.1145/2185520.2185593〉. 〈hal-00699908v4〉

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