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Oriol Rodriguez-Leor, E. Fernandez-Nofrerias, J. Mauri, C. Garcia, R. Villuendas, V. Valle, et al. (2003). Intravascular ultrasound segmentation using local binary patterns. European Heart Journal (IF: 5.997), ESC Congress 2003.
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Xavier Otazu, M. Gonzalez-Audicana, O. Fors, & J. Nuñez. (2005). Introduction of Sensor Spectral Response Into Image Fusion Methods. Application to Wavelet-Based Methods. IEEE Transactions on Geoscience and Remote Sensing, 43(10): 2376–2385 (IF: 1.627).
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Zeynep Yucel, Albert Ali Salah, Çetin Meriçli, Tekin Meriçli, Roberto Valenti, & Theo Gevers. (2013). Joint Attention by Gaze Interpolation and Saliency. T-CIBER - IEEE Transactions on cybernetics, 829–842.
Abstract: Joint attention, which is the ability of coordination of a common point of reference with the communicating party, emerges as a key factor in various interaction scenarios. This paper presents an image-based method for establishing joint attention between an experimenter and a robot. The precise analysis of the experimenter's eye region requires stability and high-resolution image acquisition, which is not always available. We investigate regression-based interpolation of the gaze direction from the head pose of the experimenter, which is easier to track. Gaussian process regression and neural networks are contrasted to interpolate the gaze direction. Then, we combine gaze interpolation with image-based saliency to improve the target point estimates and test three different saliency schemes. We demonstrate the proposed method on a human-robot interaction scenario. Cross-subject evaluations, as well as experiments under adverse conditions (such as dimmed or artificial illumination or motion blur), show that our method generalizes well and achieves rapid gaze estimation for establishing joint attention.
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Jian Yang, Alejandro F. Frangi, Jing-Yu Yang, David Zhang, & Zhong Jin. (2005). KPCA Plus LDA: A Complete Kernel Fisher Discriminant Framework for Feature Extraction and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):230–244 (IF: 3.810).
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Alicia Fornes, Josep Llados, Oriol Ramos Terrades, & Marçal Rusiñol. (2016). La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals. Lligall, Revista Catalana d'Arxivística, 20–46.
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S. Tanimoto, N. Bruining, David Rotger, Petia Radeva, J. Ligthart, R.T. van Domburg, et al. (2008). Late Stent Recoil of the Bioabsorbable Everolimus Eluting Coronary Stent and its Relationship with Stent Struts Distribution and Plaque Morphology. Journal of the American College of Cardiology, vol. 52(20):1616–1620.
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Bogdan Raducanu, & Jordi Vitria. (2008). Learning to Learn: From Smarts Machines to Intelligent Machines. PRL - Patter Recognition Letters, 1024–1032.
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Joan Serrat, Ferran Diego, & Felipe Lumbreras. (2008). Los faros delanteros a traves del objetivo. UAB Divulga, Revista de divulgacion cientifica.
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Aura Hernandez-Sabate, Meritxell Joanpere, Nuria Gorgorio, & Lluis Albarracin. (2015). Mathematics learning opportunities when playing a Tower Defense Game. IJSG - International Journal of Serious Games, 57–71.
Abstract: A qualitative research study is presented herein with the purpose of identifying mathematics learning opportunities in students between 10 and 12 years old while playing a commercial version of a Tower Defense game. These learning opportunities are understood as mathematicisable moments of the game and involve the establishment of relationships between the game and mathematical problem solving. Based on the analysis of these mathematicisable moments, we conclude that the game can promote problem-solving processes and learning opportunities that can be associated with different mathematical contents that appears in mathematics curricula, thought it seems that teacher or new game elements might be needed to facilitate the processes.
Keywords: Tower Defense game; learning opportunities; mathematics; problem solving; game design
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Cristina Cañero, Nikolaos Thomos, George A. Triantafyllid, George C. Litos, & Michael G. Strintzis. (2005). Mobile Tele-echography: User Interface Design. IEEE Transactions on Information Technology in Biomedicine, 9(1):44–49 (IF: 1.376).
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C. Alejandro Parraga, Robert Benavente, & Maria Vanrell. (2007). Modeling Colour-Naming Space with Fuzzy Sets. Perception 36:198–198, supp.
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Cristina Cañero, Petia Radeva, M. Gomez, J. Mauri, E. Fernandez-Nofrerias, Oriol Rodriguez-Leor, et al. (2002). Modelo experimental para la reconstruccion tridimensional de las arterias coronarias a partir de imagenes de coronariografia.
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O. Rodriguez, J. Mauri, E Fernandez-Nofrerias, J. Lopez, A. Tovar, R. Villuendas, et al. (2003). Modelo fisico para la simulacion de imagenes de ecografia intracoronaria. Revista Española de Cardiologia (IF: 0.959), 56(2), Congreso de las Enfermedades Cardiovasculares.
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M. Gomez, J. Mauri, E. Fernandez-Nofrerias, Oriol Rodriguez-Leor, Carme Julia, Misael Rosales, et al. (2002). Modelo fisico para la simulacion de ultrasonido Intravascular. XXXVIII Congreso Nacional de la Sociedad Española de Cardiologia..
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Sergio Escalera. (2013). Multi-Modal Human Behaviour Analysis from Visual Data Sources. ERCIM - ERCIM News journal, 21–22.
Abstract: The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction.
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