Ensemble ellipse fitting by spatial median consensus

Ellipses are among the most frequently used geometric models in visual pattern recognition and digital image analysis. This work aims to combine the outputs of an ensemble of ellipse fitting methods, so that the deleterious effect of suboptimal fits is alleviated. Therefore, the accuracy of the combined ellipse fit is higher than the accuracy of the individual methods. Three characterizations of the ellipse have been considered by different researchers: algebraic, geometric, and natural. In this paper, the natural characterization has been employed in our method due to its superior performance. Furthermore, five ellipse fitting methods have been chosen to be combined by the proposed consensus method. The experiments include comparisons of our proposal with the original methods and additional ones. Several tests with synthetic and bitmap image datasets demonstrate its great potential with noisy data and the presence of occlusion. The proposed consensus algorithm is the only one that ranks among the first positions for all the tests that were carried out. This demonstrates the suitability of our proposal for practical applications with high occlusion or noise.This work is partially supported by the Ministry of Economy and Competitiveness of Spain [grant numbers TIN2016-75097-P and PPIT.UMA.B1.2017]. It is also partially supported by the Ministry of Science, Innovation and Universities of Spain [grant number RTI2018-094645-B-I00], project name Automated detection with low-cost hardware of unusual activities in video sequences. It is also partially supported by the Autonomous Government of Andalusia (Spain) under project UMA18-FEDERJA-084, project name Detection of anomalous behavior agents by deep learning in low-cost video surveillance intelligent systems. All of them include funds from the European Regional Development Fund (ERDF). The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga. They also gratefully acknowledge the support of NVIDIA Corporation with the donation of two Titan X GPUs. The authors acknowledge the funding from the Universidad de Málaga. Funding for open access charge: Universidad de Málaga / CBUA

Diseño e implementación de una herramienta de coordinación de los títulos que se imparten en la Escuela de Ingenierías Industriales

Resumen de los autoresUniversidad de Málaga. Escuela de Ingenierías IndustrialesLa declaración de Bolonia en torno al Espacio Europeo de Educación Superior (EEES) lleva asociadas tareas de coordinación tanto a nivel horizontal como vertical para una correcta implantación de los distintos títulos universitarios. Por ello, se hace necesario el diseño y la implementación de una herramienta que, a nivel de Centro, establezca los mecanismos para adecuar las actividades docentes, facilitando la labor del profesorado, de los coordinadores de título y de la propia dirección del Centro. La Escuela de Ingenierías Industriales es el centro más grande de la Universidad de Málaga, y la coordinación imprescindible para su correcto funcionamiento. En este artículo se presenta el diseño detallado de una sala virtual bajo la plataforma Moodle, que se ha desarrollado como plan de mejora durante este curso académico.ES