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99 results on '"del Pobil, A.P."'

4. Chapter Visual Analysis of Robot and Animal Colonies

Author

Martínez, Ester and del Pobil, A.P.

Subjects
Computing & information technology, bic Book Industry Communication::U Computing & information technology::UG Graphical & digital media applications
Abstract

Graphical & digital media applications

Published
2010
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9. Crowd emotion detection using dynamic probabilistic models

Author

Baig, M.W., Barakova, E. I., Marcenaro, L., Rauterberg, G.M.W., Regazzoni, C. S., del Pobil, A.P., Chinellato, E., Martinez-Martin, E., Hallam, J., Cervera, E., Morales, A., and Industrial Design

Subjects
Collective behavior, Signal processing, Collective Behavior, Crowd Emotions Detection, Collective Behavior, Dynamic Bayesian Networks, Autobiographical Memory, Dynamic event modelling, Computer science, business.industry, Feature vector, Probabilistic logic, Space (commercial competition), Machine learning, computer.software_genre, Motion (physics), Autobiographical Memory, Crowd Emotions Detection, Dynamic event modeling, Dynamic event modelling, Artificial intelligence, Dynamic Bayesian Networks, Set (psychology), business, computer, Dynamic Bayesian network, Simulation
Abstract

Detecting emotions of a crowd to control the situation is an area of emerging interest. The purpose of this paper is to present a novel idea to detect the emotions of the crowd. Emotions are defined as evolving quantities arising from the reaction to contextual situations in a set of dynamic pattern of events. These events depend on internal and external interaction states in an already mapped space. The emotions of multiple people constituting a crowd in any surveillance environment are estimated by their social and collective behaviors using sensor signals e.g., a camera, which captures and tracks their motion. The feature space is constructed based on local features to model the contextual situations and the different interactions corresponding to different emergent behaviors are modeled using bio-inspired dynamic model. The changes in emotions correspond to behavioral changes which are produced to regulate behaviors under different encountered situations. Proposed algorithm involves the probabilistic signal processing modelling techniques for analysis of different types of collective behaviors based on interactions among people and classification models to estimate emotions as positive or negative. The evaluations are performed on simulated data show the proposed algorithm effectively recognizes the emotions of the crowd under specific situations. © 2014 Springer International Publishing Switzerland.

Published
2014

10. Development of an ecological decision support system

Author

van Beusekom, Frits, Brazier, Frances, Schipper, Piet, Treur, Jan, del Pobil, A.P., Artificial intelligence, Artificial Intelligence (section level), and Social AI

Subjects
Decision support system, SDG 16 - Peace, Operations research, Circumscription, business.industry, Computer science, Default logic, SDG 16 - Peace, Justice and Strong Institutions, Environmental resource management, Evidential reasoning approach, computer.software_genre, Justice and Strong Institutions, Expert system, Development (topology), Non-monotonic logic, business, computer
Abstract

In this paper a knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of in-homogeneous samples of plant species. Techniques from the area of non-monotonic reasoning are applied to model multi-interpretable input information.

Published
1998

34. Improving Image-Based Visual Serving with Three-Dimensional Features.

Author

Cervera, E., del Pobil, A.P., Berry, F., and Martinet, P.

Subjects
*SERVOMECHANISMS, *ROBOTICS, *TRAJECTORY optimization
Abstract

Neither of the classical visual servoing approaches, position-based and image-based, are completely satisfactory. In position-based visual servoing the trajectory of the robot is well stated, but the approach suffers mainly from the image features going out of the visual field of the cameras. On the other hand, image-based visual servoing has been found generally satisfactory and robust in the presence of camera and hand-eye calibration errors. However, in some cases, singularities and local minima may arise, and the robot can go further from its joint limits. This paper is a step towards the synthesis of both approaches with their particular advantages, i.e., the trajectory of the camera motion is predictable and the image features remain in the field of view of the camera. The basis is the introduction of three-dimensional information in the feature vector. Point depth and object pose produce useful behavior in the control of the camera. Using the task-function approach, we demonstrate the relationship between the velocity screw of the camera and the current and desired poses of the object in the camera frame. Camera calibration is assumed, at least coarsely. Experimental results on real robotic platforms illustrate the presented approach. [ABSTRACT FROM AUTHOR]

Published
2003
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