Hand gesture recognition based on morphologic features

Comunicación presentada en el IX Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Benicàssim, Mayo, 2001.

Nosocomios higienistas: el caso Florence Nightingale

Los impresionantes cambios surgidos tras el inicio de la Revolución Industrial ayudaron a que de manera reiterada se buscaran soluciones a los diferentes problemas que se sucedían, uno tras de otro, como resultado del hacinamiento y las modificaciones sociopolíticas y económicas. Los avances en el campo de la ciencia, y en particular en las ciencias de la salud, fueron innumerables, estableciéndose en la sociedad una preocupación marcada por solucionar los problemas de las clases más desfavorecidas. En el campo de la sanidad, progresivamente se fueron dejando atrás posturas ancladas en los modelos basados en los «miasmas», para pasar a fundamentarse en el modelo microbiano de la mano de Pasteur y Lister. Estos descubrimientos fueron trasladados a la arquitectura progresivamente, dando paso a edificios que buscaban mantener unas condiciones higiénicas adecuadas que exiliaran las enfermedades del interior de los «paramentos de los hospitales». Ejemplo de esta lucha fue la llevada a cabo por la enfermera Florence Nightingale, que gracias a la observación y a sus conocimientos adquiridos tanto en el Instituto de Diaconisas de Kaiserswerth en Alemania como en la Maison de la Providence de las Hermanas de la Caridad de París, logró establecer una serie de pautas que aplicó al establecimiento que gestionó, el Hospital Scutari, durante la Guerra de Crimea.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

Stability in Linear Optimization Under Perturbations of the Left-Hand Side Coefficients

This paper studies stability properties of linear optimization problems with finitely many variables and an arbitrary number of constraints, when only left hand side coefficients can be perturbed. The coefficients of the constraints are assumed to be continuous functions with respect to an index which ranges on certain compact Hausdorff topological space, and these properties are preserved by the admissible perturbations. More in detail, the paper analyzes the continuity properties of the feasible set, the optimal set and the optimal value, as well as the preservation of desirable properties (boundedness, uniqueness) of the feasible and of the optimal sets, under sufficiently small perturbations.

Poem in John Henry Tudor's hand(?), March 1796, with empty envelope

This poem is about winter and appears to be an assemblage of passages from several published works along with Tudor's own compositions. On the verso, Tudor wrote "Abbott 2nd. March 1796." On the empty envelope is written: "Letters from my dear deceased friend J.H.T.," along with a note in another hand reading: "no letters found enclosed." It is unclear whether or not the envelope formerly held the poem.