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Probabilistic simultaneous pose and non-rigid shape recovery
Moreno-Noguer, Francesc; Porta Pleite, Josep Maria
Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI; Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
We present an algorithm to simultaneously recover non-rigid shape and camera poses from point correspondences between a reference shape and a sequence of input images. The key novel contribution of our approach is in bringing the tools of the probabilistic SLAM methodology from a rigid to a deformable domain. Under the assumption that the shape may be represented as a weighted sum of deformation modes, we show that the problem of estimating the modal weights along with the camera poses, may be probabilistically formulated as a maximum a posterior estimate and solved using an iterative least squares optimization. An extensive evaluation on synthetic and real data, shows that our approach has several significant advantages over current approaches, such as performing robustly under large amounts of noise and outliers, and neither requiring to track points over the whole sequence nor initializations close from the ground truth solution.
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
Image processing
computer vision
Imatges -- Processament
Classificació INSPEC::Pattern recognition::Image recognition::Pose estimation
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
info:eu-repo/semantics/conferenceObject
         

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