An Efficient Background Term for 3D Reconstruction and Tracking with Smooth Surface Models
Autor: | Javier Gonzalez-Jimenez, Mariano Jaimez, Daniel Cremers, Thomas J. Cashman, Andrew Fitzgibbon |
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Rok vydání: | 2017 |
Předmět: |
060201 languages & linguistics
business.industry 3D reconstruction 06 humanities and the arts 02 engineering and technology Iterative reconstruction Image segmentation Computational geometry Visual hull Silhouette Video tracking 0602 languages and literature 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Distance transform Mathematics |
Zdroj: | CVPR |
Popis: | We present a novel strategy to shrink and constrain a 3D model, represented as a smooth spline-like surface, within the visual hull of an object observed from one or multiple views. This new background or silhouette term combines the efficiency of previous approaches based on an image-plane distance transform with the accuracy of formulations based on raycasting or ray potentials. The overall formulation is solved by alternating an inner nonlinear minization (raycasting) with a joint optimization of the surface geometry, the camera poses and the data correspondences. Experiments on 3D reconstruction and object tracking show that the new formulation corrects several deficiencies of existing approaches, for instance when modelling non-convex shapes. Moreover, our proposal is more robust against defects in the object segmentation and inherently handles the presence of uncertainty in the measurements (e.g. null depth values in images provided by RGB-D cameras). |
Databáze: | OpenAIRE |
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