L
Luis Jimenez-Linares
Researcher at University of Castilla–La Mancha
Publications - 29
Citations - 191
Luis Jimenez-Linares is an academic researcher from University of Castilla–La Mancha. The author has contributed to research in topics: Fuzzy logic & Series (mathematics). The author has an hindex of 7, co-authored 27 publications receiving 164 citations.
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Journal ArticleDOI
Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning
C. Solana-Cipres,G. Fernandez-Escribano,Luis Rodriguez-Benitez,Juan Moreno-Garcia,Luis Jimenez-Linares +4 more
TL;DR: A real-time segmentation algorithm to obtain moving objects from the H.264 compressed domain based on motion vectors associated to the macroblocks and decision modes that uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way.
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Intelligent surveillance based on normality analysis to detect abnormal behaviors
Javier Albusac,David Vallejo,Luis Jimenez-Linares,Jose Jesus Castro-Schez,Luis Rodriguez-Benitez +4 more
TL;DR: Intelligent surveillance refers to using Artificial Intelligence techniques in order to improve surveillance and deal with semantic information obtained from low-level security devices.
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A supervised learning approach to automate the acquisition of knowledge in surveillance systems
TL;DR: A machine learning-based method to build knowledge bases used to carry out surveillance tasks in environments monitored with video cameras that generates three sets of rules for each camera that allow to detect objects' anomalous behaviours depending on three parameters: object class, object position, and object speed.
Journal ArticleDOI
Automatic objects behaviour recognition from compressed video domain
Luis Rodriguez-Benitez,Juan Moreno-Garcia,Jose Jesus Castro-Schez,Javier Albusac,Luis Jimenez-Linares +4 more
TL;DR: A system that, directly from compressed video domain, establishes a correspondence between objects in motion in a video scene and a concrete behaviour by using linguistic variables, based on fuzzification of MPEG motion data.
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Description of multivariate time series by means of trends characterization in the fuzzy domain
TL;DR: A new method to automatically obtain linguistic descriptions from a multivariate time series using a fuzzy model called the temporal fuzzy model, which is checked in sports, more concretely, in countermovement jumping.