International audienceThis paper explores constrained convex space partition (CCSP) as a new acceleration structure for ray tracing. A CCSP is a graph, representing a space partition made up of empty convex volumes. The scene geometry is located on the boundary of the convex volumes. Therefore, each empty volume is bounded with two kinds of faces: occlusive ones (belonging to the scene geometry), and non-occlusive ones. Given a ray, ray casting is performed by traversing the CCSP one volume at a time, until it hits the scene geometry. In this paper, this idea is applied to architectural scenes. We show that CCSP allows to cast several hundreds of millions of rays per second, even if they are not spatially coherent. Experiments are performed for large furnished buildings made up of hundreds of millions of polygons and containing thousands of light sources
Motivation
The investigation of the structure of biological systems at the molecular level gives insight about their functions and dynamics. Shape and surface of biomolecules are fundamental to molecular recognition events. Characterizing their geometry can lead to more adequate predictions of their interactions. In the present work, we assess the performance of reference shape retrieval methods from the computer vision community on protein shapes.
Results
Shape retrieval methods are efficient in identifying orthologous proteins and tracking large conformational changes. This work illustrates the interest for the protein surface shape as a higher-level representation of the protein structure that 1) abstracts the underlying protein sequence, structure or fold, 2) allows the use of shape retrieval methods to screen large database of protein structures to identify surficial homologs and possible interacting partners, 3) opens an extension of the protein structure-function paradigm towards a protein structure-surface(s)-function paradigm.
Availability
All data are available online at http://datasetmachat.drugdesign.fr
Supplementary information
Supplementary data are available at Bioinformatics online.
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