Gustavo Olague

Prof. Gustavo Olague

Ensenada Center for Scientific Research and Higher Education, Ensenada, Baja California, Mexico
orcid

Research Focus & Metrics

Academic Career Length

29Years (1998-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 April 2002 in Pattern Recognition
Verified
Journal Article
Closed access
Gustavo OlagueGustavo Olague
Gustavo Olague
RMRoger Mohr
Roger Mohr

4 January 2007 in Computer Vision and Image Understanding
Verified
Journal Article
Closed access
BHBenjamín Hernández
Benjamín Hernández
Gustavo OlagueGustavo Olague
Gustavo Olague
RHRiad Hammoud
Riad Hammoud
Leonardo TrujilloLeonardo Trujillo
Leonardo Trujillo
EREva Romero
Eva Romero

1 December 2008 in Evolutionary Computation
Verified
Journal Article
Closed access
Leonardo TrujilloLeonardo Trujillo
Leonardo Trujillo
Gustavo OlagueGustavo Olague
Gustavo Olague
This work describes how evolutionary computation can be used to synthesize low-level image operators that detect interesting points on digital images. Interest point detection is an essential part of many modern computer vision systems that solve tasks such as object recognition, stereo correspondence, and image indexing, to name but a few. The design of the specialized operators is posed as an optimization/search problem that is solved with genetic programming (GP), a strategy still mostly unexplored by the computer vision community. The proposed approach automatically synthesizes operators that are competitive with state-of-the-art designs, taking into account an operator's geometric stability and the global separability of detected points during fitness evaluation. The GP search space is defined using simple primitive operations that are commonly found in point detectors proposed by the vision community. The experiments described in this paper extend previous results (Trujillo and Olague, 2006a,b) by presenting 15 new operators that were synthesized through the GP-based search. Some of the synthesized operators can be regarded as improved manmade designs because they employ well-known image processing techniques and achieve highly competitive performance. On the other hand, since the GP search also generates what can be considered as unconventional operators for point detection, these results provide a new perspective to feature extraction research.



20 January 2012 in Regional Environmental Change
Verified
Journal Article
Closed access
PDF file
MTMattia Trabucchi
Mattia Trabucchi
CPCesar Puente
Cesar Puente
FCFrancisco A. Comín
Francisco A. Comín
Gustavo OlagueGustavo Olague
Gustavo Olague
SSStephen V. Smith
Stephen V. Smith