Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46786
Title: Heuristic algorithms for fast and accurate tracking of moving objects in unrestricted environments
Authors: Sánchez-Nielsen, Elena
Hernández Tejera, Mario 
UNESCO Clasification: 1203 Ciencia de los ordenadores
Issue Date: 2005
Project: Tecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccion 
Journal: Lecture Notes in Computer Science 
Conference: 1st International Symposium on Brain, Vision, and Artificial Intelligence 
Abstract: 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.
URI: http://hdl.handle.net/10553/46786
ISBN: 978-3-540-29282-1
ISSN: 0302-9743
DOI: 10.1007/11565123_49
Source: De Gregorio M., Di Maio V., Frucci M., Musio C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg
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