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Mode-shape interpretation: Re-thinking modal space for recovering deformable shapes

AutorAgudo, Antonio ; Montiel, J. M. M.; Calvo, Begoña; Moreno-Noguer, Francesc
Fecha de publicación2016
EditorInstitute of Electrical and Electronics Engineers
CitaciónIEEE Winter Conference on Applications of Computer Vision: 1-8 (2016)
ResumenThis paper describes an on-line approach for estimating non-rigid shape and camera pose from monocular video sequences. We assume an initial estimate of the shape at rest to be given and represented by a triangulated mesh, which is encoded by a matrix of the distances between every pair of vertexes. By applying spectral analysis on this matrix, we are then able to compute a low-dimensional shape basis, that in contrast to standard approaches, has a very direct physical interpretation and requires a much smaller number of modes to span a large variety of deformations, either for inextensible or extensible configurations. Based on this low-rank model, we then sequentially retrieve both camera motion and non-rigid shape in each image, optimizing the model parameters with bundle adjustment over a sliding window of image frames. Since the number of these parameters is small, specially when considering physical priors, our approach may potentially achieve real-time performance. Experimental results on real videos for different scenarios demonstrate remarkable robustness to artifacts such as missing and noisy observations.
DescripciónTrabajo presentado al WACV 2016: IEEE Winter Conference on Applications of Computer Vision, celebrado en Lake Placid, NY(US) del 7 al 9 de marzo de 2016.
Versión del editorhttp://dx.doi.org/10.1109/WACV.2016.7477725
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