@inproceedings{82b684b31b4b409791e08350b681f1d4,
title = "Robust Bayesian fitting of 3D morphable model",
abstract = "We propose to fit automatically a 3D morphable face model to a point cloud captured with a RGB-D sensor. Both data sets, the shape model and the target point cloud are modelled as two probability density functions (pdfs). Rigid registration (rotation and translation) and reconstruction on the model is performed by minimising the Euclidean distance between these two pdfs augmented with a multivariate Gaussian prior. Our resulting process is robust and it does not require point to point correspondence. Experimental results on synthetic and real data illustrates the performance of this novel approach.",
keywords = "3D face reconstruction, L2E, RGB-D sensor, computer vision, divergence, morphable models, registration, shape fitting",
author = "Claudia Arellano and Rozenn Dahyot",
year = "2013",
doi = "10.1145/2534008.2534013",
language = "English",
isbn = "9781450325899",
series = "ACM International Conference Proceeding Series",
booktitle = "Proceedings of the 10th European Conference on Visual Media Production, CVMP 2013",
note = "10th European Conference on Visual Media Production, CVMP 2013 ; Conference date: 06-11-2013 Through 07-11-2013",
}