http://hdl.handle.net/2117/3934 Thu, 23 May 2013 17:22:16 GMT 2013-05-23T17:22:16Z webmaster.bupc@upc.edu Universitat Politècnica de Catalunya. Servei de Biblioteques i Documentació no http://hdl.handle.net/2117/19053 Title: Phase-field models in interfacial pattern formation out of equilibrium Authors: González Cinca, Ricardo; Folch, R.; Benítez Iglesias, Raúl; Ramírez de la Piscina Millán, Laureano; Casademunt, Jaume; Hernández-Machado, A. Tue, 30 Apr 2013 10:58:31 GMT http://hdl.handle.net/2117/19053 2013-04-30T10:58:31Z González Cinca, Ricardo; Folch, R.; Benítez Iglesias, Raúl; Ramírez de la Piscina Millán, Laureano; Casademunt, Jaume; Hernández-Machado, A. no http://hdl.handle.net/2117/17853 Title: Classification of mental tasks using different spectral estimation methods Authors: Diez, Pablo F.; Laciar, Eric; Mut, Vicente; Ávila, Enrique; Torres Cebrián, Abel Mon, 18 Feb 2013 15:29:32 GMT http://hdl.handle.net/2117/17853 2013-02-18T15:29:32Z Diez, Pablo F.; Laciar, Eric; Mut, Vicente; Ávila, Enrique; Torres Cebrián, Abel no http://hdl.handle.net/2117/17519 Title: Network-based control Authors: Fuertes Armengol, José Mª; Chow, Mo-Yuen; Villa Millaruelo, Ricardo; Gupta, Rachana; Ayza Graells, Jordi Fri, 25 Jan 2013 11:54:15 GMT http://hdl.handle.net/2117/17519 2013-01-25T11:54:15Z Fuertes Armengol, José Mª; Chow, Mo-Yuen; Villa Millaruelo, Ricardo; Gupta, Rachana; Ayza Graells, Jordi no http://hdl.handle.net/2117/17152 Title: Uniform sampling of rotations for discrete and continuous learning of 2D shape models Authors: Perez-Sala, Xavier; Igual, Laura; Escalera, Sergio; Angulo Bahón, Cecilio Abstract: Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. Wed, 19 Dec 2012 11:23:07 GMT http://hdl.handle.net/2117/17152 2012-12-19T11:23:07Z Perez-Sala, Xavier; Igual, Laura; Escalera, Sergio; Angulo Bahón, Cecilio no Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. http://hdl.handle.net/2117/13428 Title: Progressive design through staged evolution Authors: Téllez, Ricardo A.; Angulo Bahón, Cecilio Wed, 05 Oct 2011 11:34:37 GMT http://hdl.handle.net/2117/13428 2011-10-05T11:34:37Z Téllez, Ricardo A.; Angulo Bahón, Cecilio no http://hdl.handle.net/2117/11613 Title: PLC Control and Matlab/Simulink Simulations – A Translation Approach Authors: Martins, Joao; Lima, Celson; Grau Saldes, Antoni; Martínez García, Herminio Tue, 01 Mar 2011 18:03:48 GMT http://hdl.handle.net/2117/11613 2011-03-01T18:03:48Z Martins, Joao; Lima, Celson; Grau Saldes, Antoni; Martínez García, Herminio no http://hdl.handle.net/2117/11056 Title: Supported human autonomy for recovery and enhancement of cognitive and motor abilities using agent technologies Authors: Cortés García, Claudio Ulises; Annicchiarico, Roberta; Urdiales García, Cristina; Barrué Subirana, Cristian; Martínez Velasco, Antonio Benito; Villar, Alfredo; Caltagirone, Carlo Abstract: The goal of SHARE-it, an EU FP6 funded project, is to develop a scalable, adaptive system of add-ons to sensor and assistive technology so that they can be modularly integrated into an intelligent home environment to enhance the individuals autonomy. The system will be designed to inform and assist the user and his/her caregivers through monitoring and mobility help. Thus, we plan to contribute to the development of the next generation of assistive devices for older persons or people with disabilities so that they can be self-dependent as long as possible. We focus on add-ons to be compatible with existing technologies and to achieve an easier integration into existing systems.We also aim at adaptive systems as transparent and, consequently, as easy to use to the person as possible. Scalability is meant to include or remove devices from the system in a simple, intuitive way. SHARE-it will provide an Agent-based Intelligent Decision Support System to aid the elders. Mon, 17 Jan 2011 10:32:59 GMT http://hdl.handle.net/2117/11056 2011-01-17T10:32:59Z Cortés García, Claudio Ulises; Annicchiarico, Roberta; Urdiales García, Cristina; Barrué Subirana, Cristian; Martínez Velasco, Antonio Benito; Villar, Alfredo; Caltagirone, Carlo no Assistive technologies, Agents The goal of SHARE-it, an EU FP6 funded project, is to develop a scalable, adaptive system of add-ons to sensor and assistive technology so that they can be modularly integrated into an intelligent home environment to enhance the individuals autonomy. The system will be designed to inform and assist the user and his/her caregivers through monitoring and mobility help. Thus, we plan to contribute to the development of the next generation of assistive devices for older persons or people with disabilities so that they can be self-dependent as long as possible. We focus on add-ons to be compatible with existing technologies and to achieve an easier integration into existing systems.We also aim at adaptive systems as transparent and, consequently, as easy to use to the person as possible. Scalability is meant to include or remove devices from the system in a simple, intuitive way. SHARE-it will provide an Agent-based Intelligent Decision Support System to aid the elders. http://hdl.handle.net/2117/9181 Title: Local boosted features for pedestrian detection Authors: Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Andrade-Cetto, Juan Abstract: The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. The first one learns discriminant local features corresponding to pedestrian parts and the second one selects and combines these boosted features into a robust class classifier. In contrast of other works, our features are based on local differences over Histograms of Oriented Gradients (HoGs). Experiments carried out to a public dataset of pedestrian images show good performance with high classification rates Wed, 29 Sep 2010 17:15:00 GMT http://hdl.handle.net/2117/9181 2010-09-29T17:15:00Z Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Andrade-Cetto, Juan no The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. The first one learns discriminant local features corresponding to pedestrian parts and the second one selects and combines these boosted features into a robust class classifier. In contrast of other works, our features are based on local differences over Histograms of Oriented Gradients (HoGs). Experiments carried out to a public dataset of pedestrian images show good performance with high classification rates http://hdl.handle.net/2117/2683 Title: Unidimensional multiscale local features for object detection under rotation and mild occlusions Authors: Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Andrade-Cetto, Juan Abstract: In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogram has been used to compute local histograms in constant time. Fri, 13 Mar 2009 09:21:10 GMT http://hdl.handle.net/2117/2683 2009-03-13T09:21:10Z Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Andrade-Cetto, Juan no In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogram has been used to compute local histograms in constant time. http://hdl.handle.net/2117/2682 Title: Robust color contour object detection invariant to shadows Authors: Scandaliaris, Jorge; Villamizar Vergel, Michael Alejandro; Andrade-Cetto, Juan; Sanfeliu Cortés, Alberto Abstract: In this work a new robust color and contour based object detection method in images with varying shadows is presented. The method relies on a physics-based contour detector that emphasizes material changes and a contour-based boosted classifier. The method has been tested in a sequence of outdoor color images presenting varying shadows using two classifiers, one that learns contour object features from a simple gradient detector, and another that learns from the photometric invariant contour detector. It is shown that the detection performance of the classifier trained with the photometric invariant detector is significantly higher than that of the classifier trained with gradient detector. Fri, 13 Mar 2009 09:21:01 GMT http://hdl.handle.net/2117/2682 2009-03-13T09:21:01Z Scandaliaris, Jorge; Villamizar Vergel, Michael Alejandro; Andrade-Cetto, Juan; Sanfeliu Cortés, Alberto no color invariance, shadow removal, object detection, boosting In this work a new robust color and contour based object detection method in images with varying shadows is presented. The method relies on a physics-based contour detector that emphasizes material changes and a contour-based boosted classifier. The method has been tested in a sequence of outdoor color images presenting varying shadows using two classifiers, one that learns contour object features from a simple gradient detector, and another that learns from the photometric invariant contour detector. It is shown that the detection performance of the classifier trained with the photometric invariant detector is significantly higher than that of the classifier trained with gradient detector. http://hdl.handle.net/2117/2669 Title: Object recognition Authors: Andrade-Cetto, Juan; Villamizar Vergel, Michael Alejandro Abstract: Object recognition entails identifying instances of known objects in sensory data by searching for a match between features in a scene and features on a model. The key elements that make object recognition feasible are the use of diverse sensory input forms such as stereo imagery or range data, appropriate low level processing of the sensory input, clever object representations, and good algorithms for scene-to-model hypothesis generation and model matching. Whether data acquisition takes place using video images or range sensors, an object recognition system must pre-process the sensory data for the extraction of relevant features in the scene. Once a feature vector is obtained, the problem now is that of correspondence. Provided a training session has taken place, a search for a match between model features and scene features is performed. A consistent match and the corresponding transformation give a solution to the problem of object recognition. Fri, 13 Mar 2009 09:18:46 GMT http://hdl.handle.net/2117/2669 2009-03-13T09:18:46Z Andrade-Cetto, Juan; Villamizar Vergel, Michael Alejandro no Artificial intelligence, Automatic guided vehicles, Computer vision, Image segmentation, Image sensors, Object setection, Robot sision, Stereo image processing Object recognition entails identifying instances of known objects in sensory data by searching for a match between features in a scene and features on a model. The key elements that make object recognition feasible are the use of diverse sensory input forms such as stereo imagery or range data, appropriate low level processing of the sensory input, clever object representations, and good algorithms for scene-to-model hypothesis generation and model matching. Whether data acquisition takes place using video images or range sensors, an object recognition system must pre-process the sensory data for the extraction of relevant features in the scene. Once a feature vector is obtained, the problem now is that of correspondence. Provided a training session has taken place, a search for a match between model features and scene features is performed. A consistent match and the corresponding transformation give a solution to the problem of object recognition. http://hdl.handle.net/2117/2668 Title: A new algorithm to compute the distance between multi-dimensional histograms Authors: Serratosa Casanelles, Francesc; Sanromà Güell, Gerard; Sanfeliu Cortés, Alberto Abstract: The aim of this paper is to present a new algorithm to compute the distance between ndimensional histograms. There are some domains such as pattern recognition or image retrieval that use the distance between histograms at some step of the classification process. For this reason, some algorithms that find the distance between histograms have been proposed in the literature. Nevertheless, most of this research has been applied on one-dimensional histograms due to the computation of a distance between multi-dimensional histograms is very expensive. In this paper, we present an efficient method to compare multi dimensional histograms in O(z2), where z represents the number of bins. Fri, 13 Mar 2009 09:18:37 GMT http://hdl.handle.net/2117/2668 2009-03-13T09:18:37Z Serratosa Casanelles, Francesc; Sanromà Güell, Gerard; Sanfeliu Cortés, Alberto no multi-dimensional histogram distance, Earth movers distance, second-order random graphs The aim of this paper is to present a new algorithm to compute the distance between ndimensional histograms. There are some domains such as pattern recognition or image retrieval that use the distance between histograms at some step of the classification process. For this reason, some algorithms that find the distance between histograms have been proposed in the literature. Nevertheless, most of this research has been applied on one-dimensional histograms due to the computation of a distance between multi-dimensional histograms is very expensive. In this paper, we present an efficient method to compare multi dimensional histograms in O(z2), where z represents the number of bins. http://hdl.handle.net/2117/2666 Title: Real-time software for mobile robot simulation and experimentation in cooperative environments Authors: Corominas Murtra, Andreu; Mirats Tur, Josep Maria; Sandoval Torres, Óscar; Sanfeliu Cortés, Alberto Abstract: This paper presents the software being developed at IRI (Institut de Robotica i Informatica Industrial) for mobile robot autonomous navigation in the context of the European project URUS (Ubiquitous Robots in Urban Settings). In order that a deployed sensor network and robots operating in the environment cooperate in terms of information sharing, main requirements are real-time performance and the integration of information coming from remote machines not onboard the robot. Moreover, the project involves a group of eleven industrial and academic partners, therefore software integration issues are critical. The proposed software framework is based on the YARP middleware and has been tested in real and simulated experiments. Fri, 13 Mar 2009 09:18:18 GMT http://hdl.handle.net/2117/2666 2009-03-13T09:18:18Z Corominas Murtra, Andreu; Mirats Tur, Josep Maria; Sandoval Torres, Óscar; Sanfeliu Cortés, Alberto no mobile robot software, real-time, sensor networks This paper presents the software being developed at IRI (Institut de Robotica i Informatica Industrial) for mobile robot autonomous navigation in the context of the European project URUS (Ubiquitous Robots in Urban Settings). In order that a deployed sensor network and robots operating in the environment cooperate in terms of information sharing, main requirements are real-time performance and the integration of information coming from remote machines not onboard the robot. Moreover, the project involves a group of eleven industrial and academic partners, therefore software integration issues are critical. The proposed software framework is based on the YARP middleware and has been tested in real and simulated experiments.