Document
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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publication venue for: Real-time vision tracking algorithm
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Real-time vision tracking algorithm
crisid: 8371
doi: 10.1007/11751649_45
date time value: conference paper date 8371
has publication venue: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
most specific type: Document
estado: published
origen: scopus
page end: 421
volume: 3984 LNCS
most specific type: Conference Paper
freetext keyword: Algorithms; Computational complexity; Computer aided software engineering; Optimization; Real time systems; Robotics; Real-time object tracking; Video processing tasks; Video surveillance; Video tracking; Computer vision
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related by: authorship_54261
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page start: 412
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EI dscopus: 2-s2.0-33745963189
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related by: authorship_54260
type: Conference Paper
type: Article
abstract: Real-time object tracking is recently becoming very important in many video processing tasks. Applications like video surveillance, robotics, people tracking, etc., need reliable and economically affordable video tracking tools. Most of current available solutions are, however, computationally intensive and sometimes require expensive video hardware. In this paper, we propose a new object tracking algorithm for real-time video that relies in the combination of a similarity measure with an euclidian metric. This approach infers the trajectory of a moving object by applying a very simple optimization method which makes the tracking algorithm robust and easy to implement. Experimental results are provided to demonstrate the performance of the proposed tracking algorithm in complex real-time video sequence scenarios. © Springer-Verlag Berlin Heidelberg 2006.
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RDF description of Real-time vision tracking algorithm - http://orbis.uaslp.mx/vivo/individual/scopus8370
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date: 2026-08-27T17:55:47
publisher: vivo
type: Document

Article
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Information Content Entity
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Conference Paper
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