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Research Interests: Robot Vision, Pattern Recognition, Image Analysis, Image segmentation, Image Processing and Analysis, and 10 moreObject Recognition, Data Fusion, Color Image Segmentation, Active Vision, Pattern, Industrial Application, Graph Partitioning, Perceptual grouping, Greedy Algorithm, and Electrical And Electronic Engineering
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In order to extend the potential of application of the syntactic approach to patternrecognition, the efficient use of models capable of describing context-sensitive structuralrelationships is needed. Moreover, the ability to learn such... more
In order to extend the potential of application of the syntactic approach to patternrecognition, the efficient use of models capable of describing context-sensitive structuralrelationships is needed. Moreover, the ability to learn such models from examples isinteresting to automate as much as possible the development of applications. In thispaper, a new formalism that permits to describe a non-trivial class of context-sensitivelanguages,
The induction of regular languages (or associated recognizers) from examples hasattracted much attention from researchers. The most part of the known methods forregular grammatical inference only use positive examples. Recently, new... more
The induction of regular languages (or associated recognizers) from examples hasattracted much attention from researchers. The most part of the known methods forregular grammatical inference only use positive examples. Recently, new symbolicand neural approaches have been proposed to induce finite state automata from bothpositive and negative data. In this paper we present a type of Moore machines, thatwe call Unbiased
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This paper presents a new feature selection method and an outliers detec- tion algorithm. The presented method is based on using a genetic algorithm com- bined with a problem-specific-designed neural network. The d imensional reduc- tion... more
This paper presents a new feature selection method and an outliers detec- tion algorithm. The presented method is based on using a genetic algorithm com- bined with a problem-specific-designed neural network. The d imensional reduc- tion and the outliers detection makes the resulting dataset more suitable for training neural networks. A comparative analysis between different kind of proposed crite- ria to select the features is reported. A number of experimental results have been carried out to demonstrate the usefulness of the presented technique.
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In this paper a new methodology for inferring regular grammarsyfrom a set ofpositive and negative examples and a-priori knowledge (if available), that we havecalled active grammatical inference, is presented. The methodology is based on... more
In this paper a new methodology for inferring regular grammarsyfrom a set ofpositive and negative examples and a-priori knowledge (if available), that we havecalled active grammatical inference, is presented. The methodology is based on acombination of neural and symbolic techniques, with the interesting feature that thelearning process can be guided by the validated previous results and/or by introducingconstraints or (positive/negative)
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In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis. Instead of making an extensive review of the graph techniques in this field, we will explain how we are using... more
In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis. Instead of making an extensive review of the graph techniques in this field, we will explain how we are using these techniques in an active vision system for an autonomous mobile robot developed in the Institut de Robòtica i Informàtica Industrial
Research Interests: Robot Vision, Pattern Recognition, Image Analysis, Image segmentation, Image Processing and Analysis, and 10 moreObject Recognition, Data Fusion, Color Image Segmentation, Active Vision, Pattern, Industrial Application, Graph Partitioning, Perceptual grouping, Greedy Algorithm, and Electrical And Electronic Engineering
This work was supported by Consejo Interministerial de Ciencia y Tecnologia (CICYT), under project TAP1999-0747 ... 11. Definition of SAOCIF and Main properties A more extended discussion, and the proofs of the the-oretical results listed... more
This work was supported by Consejo Interministerial de Ciencia y Tecnologia (CICYT), under project TAP1999-0747 ... 11. Definition of SAOCIF and Main properties A more extended discussion, and the proofs of the the-oretical results listed in this section can be found in ...
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Page 1. REPRESENTATION AND RECOGNITION OF REGULAR GRAMMARS BY MEANS OF SECOND-ORDER RECURRENT NEURAL NETWORKS R. Alqu~zar 1 and A. Sanfeliu Institut de Cibernhtica (UPC - CSIC) Diagonal 647, 2a, Barcelona (Spain) ...
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Marco is the name of a research mobile robot that is being developed at the In- stituto de Robótica e Infomática Industrial of UPC-CSIC. It is designed with learn- ing abilities to acquire information about indoor environments using... more
Marco is the name of a research mobile robot that is being developed at the In- stituto de Robótica e Infomática Industrial of UPC-CSIC. It is designed with learn- ing abilities to acquire information about indoor environments using various percep- tion sensors. Marco uses video cameras and ultrasonic sensors to perceive the world, and pattern recognition and computer vision techniques
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Page 1. T. Caelli et al. (Eds.): SSPR&SPR 2002, LNCS 2396, pp. 252-262, 2002. Springer-Verlag Berlin Heidelberg 2002 Estimating the Joint Probability Distribution of Random Vertices and Arcs by Means of Second-Order Random Graphs ...
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Page 1. Efficient Recognition of a Class of Context-Sensitive Languages Described by Augmented Regular Expressions Alberto Sanfeliu 1 and Ren@ Alqu@zar 2 1 Institut de Robbtica i Inform~tica Industrial, UPC-CSIC Gran ...
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ABSTRACT The hide-and-seek game is considered an excellent domain for studying the interactions between mobile robots and humans. Prior to the implementation and test in our mobile robots TIBI and DABO, we have been devising different... more
ABSTRACT The hide-and-seek game is considered an excellent domain for studying the interactions between mobile robots and humans. Prior to the implementation and test in our mobile robots TIBI and DABO, we have been devising different models and strategies to play this game and comparing them extensively in simulations. Recently, we have proposed the use of MOMDP (Mixed Observability Markov Decision Processes) models to learn a good policy to be applied by the seeker. Even though MOMDPs reduce the computational cost of POMDPs (Partially Observable MDPs), they still have a high computational complexity which is exponential with the number of states. For the hide-and-seek game, the number of states is directly related to the number of grid cells, and for two players (the hider and the seeker), it is the square of the number of cells. As an alternative to off-line MOMDP policy computation with the complete grid fine resolution, we have devised a two-level MOMDP, where the policy is computed on-line at the top level with a reduced number of states independent of the grid size. In this paper, we introduce a new fast heuristic method for the seeker and compare its performance to both off-line and on-line MOMDP approaches. We show simulation results in maps of different sizes against two types of automated hiders.
ABSTRACT The hide-and-seek game has many interesting aspects for studying cognitive functions in robots and the interactions between mobile robots and humans. Some MOMDP (Mixed Observable Markovian Decision Processes) models and a... more
ABSTRACT The hide-and-seek game has many interesting aspects for studying cognitive functions in robots and the interactions between mobile robots and humans. Some MOMDP (Mixed Observable Markovian Decision Processes) models and a heuristic-based method are proposed and evaluated as an automated seeker. MOMDPs are used because the hider's position is not always known (partially observable), and the seeker's position is fully observable. The MOMDP model is used in an o-line method for which two reward functions are tried. Because the time complexity of this model grows exponentially with the number of (partially observable) states, an on-line hierarchical MOMDP model was proposed to handle bigger maps. To reduce the states in the on-line method a robot centered segmentation is used. In addition to extensive simulations, games with a human hider and a real mobile robot as a seeker have been done in a simple urban environment.