Identificación de rostros por técnica de puntos de interés SURF

En este trabajo se muestra un sistema de identificación de rostros a través de la técnica de extracción y análisis de los puntos de interés SURF (Speeded Up Robust Features).En esta metodología se hace uso de los puntos extraídos a partir de aplicar una partición al rostro en rejillas para obtener ventanas de la imagen, por medio de una ventana que se desliza a través de la imagen a analizar; el sistema obtiene los puntos de interés y el descriptor correspondiente a estos, para cada una de las ventanas (rejillas) de la imagen y son guardados en la base de datos de entrenamiento. Esteproblema requiere un alto costo computacional ya que para extraer 225 rejillas de una imagen y generar los descriptores, de manera secuencial tiene un alto costo computacional, por lo que también se muestra la implementación con técnicas de programación en paralelo, logrando una reducción significativa del tiempo de cómputo para hacer factible su aplicación. El sistema se probó con cuatro bases de datos de rostros y se ha alcanzado un resultado fiable.Palabra(s) Clave(s): Matching, reconocimiento de rostros, reconocimiento de patrones, puntos de interés SURF

Geometrical-based lip-reading using template probabilistic multi-dimension dynamic time warping

By identifying lip movements and characterizing their associations with speech sounds, the performance of speech recognition systems can be improved, particularly when operating in noisy environments. In this paper, we present a geometrical-based automatic lip reading system that extracts the lip region from images using conventional techniques, but the contour itself is extracted using a novel application of a combination of border following and convex hull approaches. Classification is carried out using an enhanced dynamic time warping technique that has the ability to operate in multiple dimensions and a template probability technique that is able to compensate for differences in the way words are uttered in the training set. The performance of the new system has been assessed in recognition of the English digits 0 to 9 as available in the CUAVE database. The experimental results obtained from the new approach compared favorably with those of existing lip reading approaches, achieving a word recognition accuracy of up to 71% with the visual information being obtained from estimates of lip height, width and their ratio

A novel lip geometry approach for audio-visual speech recognition

By identifying lip movements and characterizing their associations with speech sounds, the performance of speech recognition systems can be improved, particularly when operating in noisy environments. Various method have been studied by research group around the world to incorporate lip movements into speech recognition in recent years, however exactly how best to incorporate the additional visual information is still not known. This study aims to extend the knowledge of relationships between visual and speech information specifically using lip geometry information due to its robustness to head rotation and the fewer number of features required to represent movement. A new method has been developed to extract lip geometry information, to perform classification and to integrate visual and speech modalities. This thesis makes several contributions. First, this work presents a new method to extract lip geometry features using the combination of a skin colour filter, a border following algorithm and a convex hull approach. The proposed method was found to improve lip shape extraction performance compared to existing approaches. Lip geometry features including height, width, ratio, area, perimeter and various combinations of these features were evaluated to determine which performs best when representing speech in the visual domain. Second, a novel template matching technique able to adapt dynamic differences in the way words are uttered by speakers has been developed, which determines the best fit of an unseen feature signal to those stored in a database template. Third, following on evaluation of integration strategies, a novel method has been developed based on alternative decision fusion strategy, in which the outcome from the visual and speech modality is chosen by measuring the quality of audio based on kurtosis and skewness analysis and driven by white noise confusion. Finally, the performance of the new methods introduced in this work are evaluated using the CUAVE and LUNA-V data corpora under a range of different signal to noise ratio conditions using the NOISEX-92 dataset