Multi-View Dynamic Shape Refinement Using Local Temporal Integration

Vincent Leroy 1 Jean-Sébastien Franco 1 Edmond Boyer 1
1 MORPHEO - Capture and Analysis of Shapes in Motion
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We consider 4D shape reconstructions in multi-view environments and investigate how to exploit temporal redundancy for precision refinement. In addition to being beneficial to many dynamic multi-view scenarios this also enables larger scenes where such increased precision can compensate for the reduced spatial resolution per image frame. With precision and scalability in mind, we propose a symmetric (non-causal) local time-window geometric integration scheme over temporal sequences, where shape reconstructions are refined framewise by warping local and reliable geometric regions of neighboring frames to them. This is in contrast to recent comparable approaches targeting a different context with more compact scenes and real-time applications. These usually use a single dense volumetric update space or geometric template, which they causally track and update globally frame by frame, with limitations in scalability for larger scenes and in topology and precision with a template based strategy. Our templateless and local approach is a first step towards temporal shape super-resolution. We show that it improves reconstruction accuracy by considering multiple frames. To this purpose, and in addition to real data examples, we introduce a multi-camera synthetic dataset that provides ground-truth data for mid-scale dynamic scenes.
Type de document :
Communication dans un congrès
IEEE, International Conference on Computer Vision 2017, Oct 2017, Venice, Italy. ICCV'17, 〈〉
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Contributeur : Vincent Leroy <>
Soumis le : mardi 29 août 2017 - 18:10:17
Dernière modification le : mercredi 6 septembre 2017 - 01:08:22



  • HAL Id : hal-01567758, version 2



Vincent Leroy, Jean-Sébastien Franco, Edmond Boyer. Multi-View Dynamic Shape Refinement Using Local Temporal Integration. IEEE, International Conference on Computer Vision 2017, Oct 2017, Venice, Italy. ICCV'17, 〈〉. 〈hal-01567758v2〉



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