Elements of information theory
Elements of information theory
A review of statistical data association for motion correspondence
International Journal of Computer Vision
Active vision for reliable ranging: cooperating focus, stereo, and vergence
International Journal of Computer Vision
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
Neural Network Perception for Mobile Robot Guidance
Neural Network Perception for Mobile Robot Guidance
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Joint Probabilistic Techniques for Tracking Multi-Part Objects
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
| Hi-index | 0.00 |
This paper describes a new approach for the creation of an adaptive system able to selectively combine dynamic multidimensional information sources to perform state estimation. The system proposed is based on an intelligent agent paradigm. Each information source is implemented as an agent that is able to adapt its behavior according to the relevant task and environment constraints. The adaptation is provided by a local self-evaluation function on each agent. Cooperation among the agents is given by a probabilistic scheme that integrates the evidential information provided by them. The proposed system aims to achieve two highly desirable attributes of an engineering system: robustness and efficiency. By combining the outputs of multiple vision modules the assumptions and constrains of each module can be factored out to result in a more robust system overall. Efficiency is still kept through the on-line selection and specialization of the agents. An initial implementation for the case of visual information demonstrates the advantages of the approach for two frequent problems faced by a mobile robot: dynamic target tracking and obstacle detection.