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- Xuming He, Richard S. Zemel, Miguel Á. Carreira-Perpiñán
- Proceedings of the 2004 IEEE Computer Society…
- 2004

We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a probabilistic framework, which combines the outputs of several components. Components differ in the information they encode. Some focus on the image-label mapping, while others… (More)

We introduce Coherent Point Drift (CPD), a novel probabilistic method for nonrigid registration of point sets. The registration is treated as a Maximum Likelihood (ML) estimation problem with motion coherence constraint over the velocity field such that one point set moves coherently to align with the second set. We formulate the motion coherence constraint… (More)

- Miguel Á. Carreira-Perpiñán, Geoffrey E. Hinton
- AISTATS
- 2005

Maximum-likelihood (ML) learning of Markov random fields is challenging because it requires estimates of averages that have an exponential number of terms. Markov chain Monte Carlo methods typically take a long time to converge on unbiased estimates, but Hinton (2002) showed that if the Markov chain is only run for a few steps, the learning can still work… (More)

- Zhengdong Lu, Miguel Á. Carreira-Perpiñán
- 2008 IEEE Conference on Computer Vision and…
- 2008

Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as K-means, little progress has been made in combining them with spectral clustering. The major challenge in designing an effective constrained spectral clustering is a sensible… (More)

- Varick L. Erickson, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
- Proceedings of the 10th ACM/IEEE International…
- 2011

Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum occupancy rather than actual usage. As a result, rooms are often over-conditioned needlessly. Thus, in order to achieve efficient conditioning, we require knowledge of occupancy. This paper shows how… (More)

- Miguel Á. Carreira-Perpiñán
- IEEE Transactions on Pattern Analysis and Machine…
- 2007

The mean-shift algorithm, based on ideas proposed by Fukunaga and Hosteller, is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density estimate. Mean-shift can be used as a nonparametric clustering method and has attracted recent attention in computer vision applications such as image segmentation or tracking. We show that,… (More)

- Miguel Á. Carreira-Perpiñán
- ICML
- 2006

We revisit Gaussian blurring mean-shift (GBMS), a procedure that iteratively sharpens a dataset by moving each data point according to the Gaussian mean-shift algorithm (GMS). (1) We give a criterion to stop the procedure as soon as clustering structure has arisen and show that this reliably produces image segmentations as good as those of GMS but much… (More)

- Miguel Á. Carreira-Perpiñán
- ICML
- 2010

We propose a new dimensionality reduction method, the elastic embedding (EE), that optimises an intuitive, nonlinear objective function of the low-dimensional coordinates of the data. The method reveals a fundamental relation betwen a spectral method, Laplacian eigenmaps, and a nonlinear method, stochastic neighbour embedding; and shows that EE can be seen… (More)

- Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
- 2015 IEEE Conference on Computer Vision and…
- 2015

An attractive approach for fast search in image databases is binary hashing, where each high-dimensional, real-valued image is mapped onto a low-dimensional, binary vector and the search is done in this binary space. Finding the optimal hash function is difficult because it involves binary constraints, and most approaches approximate the optimization by… (More)

- Miguel A Carreira-Perpiñán, Richard J Lister, Geoffrey J Goodhill
- Cerebral cortex
- 2005

Primary visual cortex contains multiple maps of features of the visual scene, including visual field position, orientation, direction, ocular dominance and spatial frequency. The complex relationships between these maps provide clues to the strategies the cortex uses for representing and processing information. Here we simulate the combined development of… (More)