This paper considers humming-based human verification and identification systems. Humming of a target person is modeled as a Gaussian mixture model, and the matching score betwe...
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
This paper presents a novel Gaussianized vector representation for scene images by an unsupervised approach. First, each image is encoded as an ensemble of orderless bag of featur...
Hao Tang, Mark Hasegawa-Johnson, Thomas S. Huang, ...
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
In this paper we evaluate the effectiveness of two likelihood normalization techniques, the Background Model Set (BMS) and the Universal Background Model (UBM), for improving perf...
Over the years, researchers in the image analysis community have successfully used various statistical modeling methods to segment, classify, and annotate digital images. In this ...
It has been recently discovered that a faithful representation for the shape of some simple distributions can be constructed using invariant statistics [1, 2]. In this paper, we c...
Abstract. Estimating a camera pose given a set of 3D-object and 2Dimage feature points is a well understood problem when correspondences are given. However, when such correspondenc...
Francesc Moreno-Noguer, Vincent Lepetit, Pascal Fu...
In this paper we are interested in finding images of people on the web, and more specifically within large databases of captioned news images. It has recently been shown that visua...