A batch Algorithm for Implicit Non-Rigid Shape and Motion Recovery
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
The recovery of 3D shape and camera motion for non-rigid scenes from single-camera video footage is a very important problem in computer vision. The low-rank shape model consists in regarding the deformations as linear combinations of basis shapes. Most algorithms for reconstructing the parameters of this model along with camera motion are based on three main steps. Given point tracks and the rank, or equivalently the number of basis shapes, they factorize a measurement matrix containing all point tracks, from which the camera motion and basis shapes are extracted and refined in a bundle adjustment manner. There are several issues that have not been addressed yet, among which, choosing the rank automatically and dealing with erroneous point tracks and missing data.
We introduce theoretical and practical contributions that address these issues. We propose an implicit imaging model for non-rigid scenes from which we derive non-rigid matching tensors and closure constraints. We give a non-rigid Structure-From-Motion algorithm based on computing matching tensors over subsequences, from which the implicit cameras are extrated. Each non-rigid matching tensor is computed, along with the rank of the subsequence, using a robust estimator incorporating a model selection criterion that detects erroneous image points.
Preliminary experimental results on real and simulated data show that our algorithm deals with challenging video sequences.
|Dynamical Vision : ICCV 2005 and ECCV 2006 workshops, WDV 2005 and WDV 2006, Beijing, China, October 21, 2005, Graz, Austria, May 13, . Revised papers 2006
|Rene Vidal, Anders Heyden, Yi Ma
|Udgivet - 2007
|Workshop of Dynamical Models for Computer Vision at IEEE International Conference on Computer Vision (ICCV) - Beijing, Kina
Varighed: 21 okt. 2005 → …
Konferencens nummer: 10
|Workshop of Dynamical Models for Computer Vision at IEEE International Conference on Computer Vision (ICCV)
|21/10/2005 → …
|Lecture notes in computer science