Useful computer vision techniques for human-robot interaction

[ES]This paper describes some simple but useful computer vision techniques for human-robot interaction. First, an omnidirectional camera setting is described that can detect people in the surroundings of the robot, giving their angular positions and a rough estimate of the distance. The device can be easily built with inexpensive components. Second, we comment on a color-based face detection technique that can alleviate skin-color false positives. Third, a simple head nod and shake detector is described, suitable for detecting affirmative/negative, approval/dissaproval, understanding/disbelief head gestures.

Fast and accurate hand pose detection for human-robot interaction

[EN]Enabling natural human-robot interaction using computer vision based applications requires fast and accurate hand detection. However, previous works in this field assume different constraints, like a limitation in the number of detected gestures, because hands are highly complex objects difficult to locate. This paper presents an approach which integrates temporal coherence cues and hand detection based on wrists using a cascade classifier. With this approach, we introduce three main contributions: (1) a transparent initialization mechanism without user participation for segmenting hands independently of their gesture, (2) a larger number of detected gestures as well as a faster training phase than previous cascade classifier based methods and (3) near real-time performance for hand pose detection in video streams.

CASIMIRO: a robot head for human-computer interaction

The physical appearance and behavior of a robot is an important asset in terms of Human-Computer Interaction. Multimodality is also fundamental, as we humans usually expect to interact in a natural way with voice, gestures, etc. People approach complex interaction devices with stances similar to those used in their interaction with other people. In this paper we describe a robot head, currently under development, that aims to be a multimodal (vision, voice, gestures,...) perceptual user interface.

LeeMed

[ES] La irrupción actual de los teléfonos inteligentes (smartphones) equipados con diversos sensores y herramientas nativas, propicia la posibilidad de crear una gran gama de aplicaciones para mejorar la vida de personas con discapacidades. Con este proyecto se pretende cubrir estos objetivos: explorar las distintas posibilidades que ofrece la plataforma Android para implementar métodos de interacción hombre-máquina adaptados a personas con discapacidad visual. Identificar las problemáticas que afectan a las personas con discapacidad visual en el ámbito sociosanitario. Desarrollar una aplicación de carácter social que contribuya a mejorar la calidad de vida de estas personas. Como resultado del trabajo, se ha desarrollado una aplicación software llamada LeeMed, que consiste en una app para la plataforma Android, dirigida a personas con discapacidad visual, para la consulta de prospectos de medicamentos a través de múltiples interfaces humanas. El trabajo ha abordado tres tipos de interfaces: la oral (órdenes de voz), la gestual y la convencional de menús y opciones (GUI)

Smile detection for user interfaces

[EN]Perceptual User Interfaces (PUIs) aim at facilitating human-computer interaction with the aid of human-like capacities (computer vision, speech recognition, etc.). In PUIs, the human face is a central element, since it conveys not only identity but also other important information, particularly with respect to the user’s mood or emotional state. This paper describes both a face detector and a smile detector for PUIs. Both are suitable for real-time interaction.

Entorno de simulación aplicado al estudio, comprensión y control del fenómeno de la realimentación acústica

[ES]El diseño de entornos de simulación aplicados al estudio, aprendizaje y adquisición de competencias es un campo de trabajo activo en todos los niveles educativos. Los sucesivos avances experimentados por las Tecnologías de la Información y Comunicaciones (TIC), las plataformas que las sustentan y los estudios e investigaciones llevadas a cabo en el campo de la Interacción Persona Ordenador (Human Computer Interaction, HCI), soportan y hacen posible la realización de herramientas como la que aquí proponemos. Se trata de un entorno de simulación que ha sido diseñado con dos grandes objetivos: fomentar el aprendizaje activo y mejorar el rendimiento académico, como los más destacados. Para ello hemos elegido la Realimentación Acústica en los sistemas de refuerzo sonoro, fenómeno que exige un estudio detallado de los parámetros que lo controlan, que presentado de la forma que aquí proponemos permitirá un mejor aprovechamiento del escaso tiempo disponible para la experimentación en situaciones reales.

Eyewear selector

[EN]The widespread availability of portable computing power and inexpensive digital cameras is opening up new possibilities for retailers. One example is in optical shops, where a number of systems exist that facilitate eyeglasses selection. These systems are now more necessary as the market is saturated with an increasingly complex array of lenses, frames, coatings, tints, photochromic and polarizing treatments, etc. Research challenges encompass Computer Vision, Multimedia and Human-Computer Interaction. Cost factors are also of importance for widespread product acceptance. This paper describes a low-cost system that allows the user to visualize di erent spectacle models in live video. The user can also move the spectacles to adjust its position on the face. Experiments show the potential of the system.

Fast classification in incrementally growing spaces

[EN]The classification speed of state-of-the-art classifiers such as SVM is an important aspect to be considered for emerging applications and domains such as data mining and human-computer interaction. Usually, a test-time speed increase in SVMs is achieved by somehow reducing the number of support vectors, which allows a faster evaluation of the decision function. In this paper a novel approach is described for fast classification in a PCA+SVM scenario. In the proposed approach, classification of an unseen sample is performed incrementally in increasingly larger feature spaces. As soon as the classification confidence is above a threshold the process stops and the class label is retrieved...