Loading...
Please wait, while we are loading the content...
Similar Documents
RAPS: Robust and Efficient Automatic Construction of Person-Specific Deformable Models
| Content Provider | CiteSeerX |
|---|---|
| Abstract | The construction of Facial Deformable Models (FDMs) is a very challenging computer vision problem, since the face is a highly deformable object and its appearance dras-tically changes under different poses, expressions, and il-luminations. Although several methods for generic FDMs construction, have been proposed for facial landmark local-ization in still images, they are insufficient for tasks such as facial behaviour analysis and facial motion capture where perfect landmark localization is required. In this case, person-specific FDMs (PSMs) are mainly employed, requir-ing manual facial landmark annotation for each person and person-specific training. In this paper, a novel method for the automatic construc-tion of PSMs is proposed. To this end, an orthonormal sub-space which is suitable for facial image reconstruction is learnt. Next, to correct the fittings of a generic model, im-age congealing (i.e., batch image aliment) is performed by employing only the learnt orthonormal subspace. Finally, the corrected fittings are used to construct the PSM. The image congealing problem is solved by formulating a suit-able sparsity regularized rank minimization problem. The proposed method outperforms the state-of-the art methods that is compared to, in terms of both landmark localization accuracy and computational time. 1. |
| File Format | |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
