Automatic (data-based) learning of expressive indicators for machine failure detection : a proposal

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Project-based learning using robots with open-source hardware and software

[EN]One of the main issues of the current education system is the lack of student motivation. This aspect together with the permanent change that the Information and Communications Technologies involve represents a major challenge for the teacher: to continuously update contents and to keep awake the student’s interest. A tremendously useful tool in classrooms consists on the integration of projects with participative and collaborative dynamics, where the teacher acts mainly as a guidance to the student activity instead of being a mere knowledge and evaluation transmitter. As a specific example of project based learning, the EDUROVs project consists on building an economic underwater robot using low cost materials, but allowing the integration and programming of many accessories and sensors with minimum budget using opensource hardware and software.

Discontinuity preserving in TV-L1 optical flow methods

[EN] We analyze the discontinuity preserving problem in TV-L1 optical flow methods. This type of methods typically creates rounded effects at flow boundaries, which usually do not coincide with object contours. A simple strategy to overcome this problem consists in inhibiting the diffusion at high image gradients. In this work, we first introduce a general framework for TV regularizers in optical flow and relate it with some standard approaches. Our survey takes into account several methods that use decreasing functions for mitigating the diffusion at image contours. Consequently, this kind of strategies may produce instabilities in the estimation of the optical flows. Hence, we study the problem of instabilities and show that it actually arises from an ill-posed formulation. From this study, it is possible to come across with different schemes to solve this problem. One of these consists in separating the pure TV process from the mitigating strategy. This has been used in another work and we demonstrate here that it has a good performance. Furthermore, we propose two alternatives to avoid the instability problems: (i) we study a fully automatic approach that solves the problem based on the information of the whole image; (ii) we derive a semi-automatic approach that takes into account the image gradients in a close neighborhood adapting the parameter in each position. In the experimental results, we present a detailed study and comparison between the different alternatives. These methods provide very good results, especially for sequences with a few dominant gradients. Additionally, a surprising effect of these approaches is that they can cope with occlusions. This can be easily achieved by using strong regularizations and high penalizations at image contours.