Programming Assignment of Programming 3: an Object-Oriented Version of Conway’s Game of Life

These are the instructions for a programming assignment of the subject Programming 3 taught at University of Alicante in Spain. The objective of the assignment is to build an object-oriented version of Conway's game of life in Java. The assignment is divided into four sub-assignments.

New framework for score segmentation and analysis in OpenMusic

We present new tools for the segmentation and analysis of musical scores in the OpenMusic computer-aided composition environment. A modular object-oriented framework enables the creation of segmentations on score objects and the implementation of automatic or semi-automatic analysis processes. The analyses can be performed and displayed thanks to customizable classes and callbacks. Concrete examples are given, in particular with the implementation of a semi-automatic harmonic analysis system and a framework for rhythmic transcription.

Personalización de aplicaciones en OO-H

Comunicación presentada en las V Jornadas Iberoamericanas de Ingeniería de Requisitos y Ambientes Software (IDEAS’02), La Habana, Cuba, abril 2002.

Modelado conceptual de aplicaciones adaptivas y proactivas en OO-H

Comunicación presentada en las VII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2002), dentro del II Taller sobre Ingeniería del Software Orientada al Web (Web Engineering) WebE'2002, El Escorial, Madrid, 19 noviembre 2002.

Modelado de estrategias de personalización en OO-H

The consideration of personalization politics in the context of any web application modelling method obliges to the revision of its different modelling activities, which must be adapted to take into account the information regarding the user (usually gathered in a user model) to define aspects such as navigation or presentation. Additionally, they must provide a set of techniques to populate such user model. Finally, and because of the rapid pace at which personalization politics usually change, the modelling process should provide support not only for static personalization rules (known at design time) but also for the definition or change of these rules once the application has been deployed. This article presents, in the context of the Object Oriented Hypermedia Method (OO-H), a personalization framework that fulfils these requirements, and is organized around four main concepts: (1) a set of design activities that capture the personalization requirements known at design time, (2) a mechanism for the specification of personalization rules, defined by means of an XML template, that decouples the definition of the personalization model from the remaining models, (3) an execution architecture that supports the change at execution time of these rules and (4) an extensible repository that includes a set of register mechanisms for the user activity in the system. The possibility of extension of this repository facilitates its adaptation to the particular characteristics of any particular application.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.