Towards the Development of Training Tools for Face Recognition

Distinctiveness plays an important role in the recognition of faces, i.e., a distinctive face is usually easier to remember than a typical face in a recognition task. This distinctiveness effect explains why caricatures are recognized faster and more accurately than unexaggerated (i.e., veridical) faces. Furthermore, using caricatures during training can facilitate recognition of a person’s face at a later time. The objective of this thesis is to determine the extent to which photorealistic computer-generated caricatures may be used in training tools to improve recognition of faces by humans. To pursue this objective, we developed a caricaturization procedure for three-dimensional (3D) face models, and characterized face recognition performance (by humans) through a series of perceptual studies. The first study focused on 3D shape information without texture. Namely, we tested whether exposure to caricatures during an initial familiarization phase would aid in the recognition of their veridical counterparts at a later time. We examined whether this effect would emerge with frontal rather than three-quarter views, after very brief exposure to caricatures during the learning phase and after modest rotations of faces during the recognition phase. Results indicate that, even under these difficult training conditions, people are more accurate at recognizing unaltered faces if they are first familiarized with caricatures of the faces, rather than with the unaltered faces. These preliminary findings support the use of caricatures in new training methods to improve face recognition. In the second study, we incorporated texture into our 3D models, which allowed us to generate photorealistic renderings. In this study, we sought to determine the extent to which familiarization with caricaturized faces could also be used to reduce other-race effects (e.g., the phenomenon whereby faces from other races appear less distinct than faces from our own race). Using an old/new face recognition paradigm, Caucasian participants were first familiarized with a set of faces from multiple races, and then asked to recognize those faces among a set of confounders. Participants who were familiarized with and then asked to recognize veridical versions of the faces showed a significant other-race effect on Indian faces. In contrast, participants who were familiarized with caricaturized versions of the same faces, and then asked to recognize their veridical versions, showed no other-race effects on Indian faces. This result suggests that caricaturization may be used to help individuals focus their attention to features that are useful for recognition of other-race faces. The third and final experiment investigated the practical application of our earlier results. Since 3D facial scans are not generally available, here we also sought to determine whether 3D reconstructions from 2D frontal images could be used for the same purpose. Using the same old/new face recognition paradigm, participants who were familiarized with reconstructed faces and then asked to recognize the ground truth versions of the faces showed a significant reduction in performance compared to the previous study. In addition, participants who were familiarized with caricatures of reconstructed versions, and then asked to recognize their corresponding ground truth versions, showed a larger reduction in performance. Our results suggest that, despite the high level of photographic realism achieved by current 3D facial reconstruction methods, additional research is needed in order to reduce reconstruction errors and capture the distinctive facial traits of an individual. These results are critical for the development of training tools based on computer-generated photorealistic caricatures from “mug shot” images

Egocentric Computer Vision and Machine Learning for Simulated Prosthetic Vision

Las prótesis visuales actuales son capaces de proporcionar percepción visual a personas con cierta ceguera. Sin pasar por la parte dañada del camino visual, la estimulación eléctrica en la retina o en el sistema nervioso provoca percepciones puntuales conocidas como “fosfenos”. Debido a limitaciones fisiológicas y tecnológicas, la información que reciben los pacientes tiene una resolución muy baja y un campo de visión y rango dinámico reducido afectando seriamente la capacidad de la persona para reconocer y navegar en entornos desconocidos. En este contexto, la inclusión de nuevas técnicas de visión por computador es un tema clave activo y abierto. En esta tesis nos centramos especialmente en el problema de desarrollar técnicas para potenciar la información visual que recibe el paciente implantado y proponemos diferentes sistemas de visión protésica simulada para la experimentación.Primero, hemos combinado la salida de dos redes neuronales convolucionales para detectar bordes informativos estructurales y siluetas de objetos. Demostramos cómo se pueden reconocer rápidamente diferentes escenas y objetos incluso en las condiciones restringidas de la visión protésica. Nuestro método es muy adecuado para la comprensión de escenas de interiores comparado con los métodos tradicionales de procesamiento de imágenes utilizados en prótesis visuales.Segundo, presentamos un nuevo sistema de realidad virtual para entornos de visión protésica simulada más realistas usando escenas panorámicas, lo que nos permite estudiar sistemáticamente el rendimiento de la búsqueda y reconocimiento de objetos. Las escenas panorámicas permiten que los sujetos se sientan inmersos en la escena al percibir la escena completa (360 grados).En la tercera contribución demostramos cómo un sistema de navegación de realidad aumentada para visión protésica ayuda al rendimiento de la navegación al reducir el tiempo y la distancia para alcanzar los objetivos, incluso reduciendo significativamente el número de colisiones de obstáculos. Mediante el uso de un algoritmo de planificación de ruta, el sistema encamina al sujeto a través de una ruta más corta y sin obstáculos. Este trabajo está actualmente bajo revisión.En la cuarta contribución, evaluamos la agudeza visual midiendo la influencia del campo de visión con respecto a la resolución espacial en prótesis visuales a través de una pantalla montada en la cabeza. Para ello, usamos la visión protésica simulada en un entorno de realidad virtual para simular la experiencia de la vida real al usar una prótesis de retina. Este trabajo está actualmente bajo revisión.Finalmente, proponemos un modelo de Spiking Neural Network (SNN) que se basa en mecanismos biológicamente plausibles y utiliza un esquema de aprendizaje no supervisado para obtener mejores algoritmos computacionales y mejorar el rendimiento de las prótesis visuales actuales. El modelo SNN propuesto puede hacer uso de la señal de muestreo descendente de la unidad de procesamiento de información de las prótesis retinianas sin pasar por el análisis de imágenes retinianas, proporcionando información útil a los ciegos. Esté trabajo está actualmente en preparación.<br /

Sources of the communicative body

This study provides evidence for the warranted assertion that classroom practices will be enhanced by awareness of how non-linguistic modalities of the face, hands and vocal intonation contribute to cohesive and cooperative strategies within social groups. Both the history and observations of non-linguistic communication presented by this study suggest that visual, kinesic, and spatial comprehension create and influence social fields and common spaces, yet our language for these fields and spaces is impoverished. This knowledge has been submerged and marginalized through history. At the same time, through time, despite this submersion and marginalization, interrelational and intrarelational synchrony and dis-synchrony, centered on and by the communicative body, occur in social settings in ways that can be considered from both historical and observational perspectives. Buildi ng on recent theory by Damasio, Donald, Noddings, Grumet, Terdiman, and Nussbaum, the historical concepts and classroom observations presented here evidence that social values such as caring, loyalty, and generosity are sometimes understood, implicitly and explicitly, through the exchange, perception, and interpretation of non-linguistic signs. By understanding how the face and hands and rhythm and pitch of the voice create cohesive and cooperative social values in learning spaces - separate from racial, ethnic, and intellectual differences - this investigation recovers a submerged knowledge in order to offer a new logic for understanding social process. In turn, this new logic hopes to further transformational practice in the learning and teaching arts and sciences