Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elements of information theory
Elements of information theory
Computer vision in the interface
Communications of the ACM - Multimodal interfaces that flex, adapt, and persist
IEICE - Transactions on Information and Systems
ISIDIS: an intelligent videosurveillance system
Proceedings of the International Working Conference on Advanced Visual Interfaces
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Tracking of objects is a basic process in computer vision. This process can be formulated as exploration problems and thus can be expressed as a search into a states space based representation approach. However, these problems are hard of solving because they involve search through a high dimensional space corresponding to the possible motion and deformation of the object. In this paper, we propose a heuristic algorithm that combines three features in order to compute motion efficiently: (1) a quality of function match, (2) Kullback-Leibler measure as heuristic to guide the search process and (3) incorporation of target dynamics for computing promising search alternatives. Once target 2D motion has been calculated, the result value of the quality of function match computed is used in other heuristic algorithm with the purpose of verifying template updates. Also, a short-term memory subsystem is included with the purpose of recovering previous views of the target object. The paper includes experimental evaluations with video streams that illustrate the efficiency for real-time vision based-tasks.