The evolution of gender inequality in tourism employment in Spain

Evolución de la desigualdad por género del empleo turístico en España. Si bien la inversión en capital laboral femenino en la industria turística ha aumentado en los últimos años y parece que la discriminación en el acceso a puestos directivos ha descendido, se siguen produciendo diferentes situaciones de desigualdad. La mujer mantiene un salario por debajo del hombre y han aparecido nuevas formas de segregación ocupacional entre hombres y mujeres e incluso entre las propias mujeres: la división entre trabajo a tiempo parcial y completo es un buen ejemplo de este proceso. La hipótesis que se plantea este trabajo es que esa combinación entre tiempo de trabajo remunerado (ámbito público) y no remunerado (ámbito privado, doméstico) es un obstáculo que provoca el acceso de los varones a empleos hasta ahora "femeninos"; así mismo, se observará la calidad del empleo turístico desde la perspectiva de género.

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.