We present a Random Sampling Consensus (RANSAC) based training approach for the problem of speaker state recognition from spontaneous speech. Our system is trained and tested with the INTERSPEECH 2011 Speaker State Challenge corpora that includes the Intoxication and the Sleepiness Subchallenges, where each sub-challenge defines a two-class classification task. We aim to perform a RANSAC-based ...

The random sample consensus (RANSAC) algorithm, along with its many cousins such as MSAC and MLESAC, has become a standard choice for robust estimation in many computer vision problems. Recently, a raft of modifications to the basic RANSAC algorithm have been proposed aimed at improving its efficiency. Many of these optimizations work by reducing the number of hypotheses that need to be evaluat...

In this paper we address the problem of classifying objects where some of the labels in the training data are noisy. This is a common scenario and can be caused by the difficulty of annotation or inadvertently due to human error. In this paper, we consider the wrongly annotated examples to be outliers and try to formulate a robust outlier identification algorithm. The task of learning a model i...

We present a robust method of image points sampling used in ransac for a class of omnidirectional cameras (view angle above 180) possessing central projection to obtain simultaneous estimation of a camera model and epipolar geometry. We focus on problem arising in ransac based estimation technique for omnidirectional images when the most of correspondences are established near the center of vie...

In this paper, we focus on the 3D SC model reconstruction from data with wide azimuthal aperture at a single elevation. Since the existing method is difficult to implement for high-frequency signal or large-size target, we propose a modified RANSAC method for the extraction. In our approach, the 3D positions of the SCs are estimated from the 1D SCs via a modified RANSAC method. Then the scatter...

This report describes how blob features can be used for automatic estimation of the fundamental matrix from two perspective projections of a 3D scene. Blobs are perceptually salient, homogeneous, compact image regions. They are represented by their average colour, area, centre of gravity and inertia matrix. Coarse blob correspondences are found by voting using colour and local similarity transf...

In this paper, a robust technique based on a genetic algorithm is proposed for estimating two-view epipolar-geometry of uncalibrated perspective stereo images from putative correspondences containing a high percentage of outliers. The advantages of this technique are three-fold: (i) replacing random search with evolutionary search applying new strategies of encoding and guided sampling; (ii) ro...

There is an increasing interest of the scientific community in the generation of 3D facade models from terrestrial laser scanner (TLS) data. The segmentation of building facades is one of the essential tasks to be carried out in a 3D modelling process. Since in reality, majority of facade components are planar, the detection and segmentation of geometric elements like planes respond to the prev...

The intelligent use of green and renewable energies requires reliable preferably anticipated information regarding their availability the behavior meteorological variables in a scenario natural intermittency. Examples this are smart grids, which can incorporate, among others, charging system for electric vehicles modern predictive management techniques. However, some issues associated with such...

Gomes Neto, Severino. Natal, 2014. 98p. PhD. Thesis. Departamento de Informática e Matemática Aplicada, Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte. The camera motion estimation represents one of the fundamental problems in Computer Vision and it may be solved by several methods. Preemptive RANSAC is one of them, which in spite of its robustness and speed p...