@inproceedings{d7a79870b67f41b09d38efb0f63efc0b,
title = "Mean shift algorithm for robust rigid registration between gaussian mixture models",
abstract = "We present a Mean shift (MS) algorithm for solving the rigid point set transformation estimation [1]. Our registration algorithm minimises exactly the Euclidean distance between Gaussian Mixture Models (GMMs). We show experimentally that our algorithm is more robust than previous implementations [1], thanks to both using an annealing framework (to avoid local extrema) and using variable bandwidths in our density estimates. Our approach is applied to 3D real data sets captured with a Lidar scanner and Kinect sensor.",
keywords = "Gaussian Mixture Models, Mean Shift, Registration, Rigid Transformation",
author = "Claudia Arellano and Rozenn Dahyot",
year = "2012",
language = "English",
isbn = "9781467310680",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
pages = "1154--1158",
booktitle = "Proceedings of the 20th European Signal Processing Conference, EUSIPCO 2012",
note = "20th European Signal Processing Conference, EUSIPCO 2012 ; Conference date: 27-08-2012 Through 31-08-2012",
}