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Local Grayvalue Invariants for Image Retrieval
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International Journal of Computer Vision
Evaluation of Interest Point Detectors
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International Journal of Computer Vision
Synthesis of interest point detectors through genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Preface: Introduction to the special issue on evolutionary computer vision and image understanding
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Using Evolution to Learn How to Perform Interest Point Detection
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Scale Invariance for Evolved Interest Operators
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Proceedings of the 12th annual conference on Genetic and evolutionary computation
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Interest point detection in images using complex network analysis
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Interest point detection through multiobjective genetic programming
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Proceedings of the 14th annual conference on Genetic and evolutionary computation
Convergence analysis of evolutionary algorithms in the presence of crash-faults and cheaters
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Customizable execution environments for evolutionary computation using BOINC + virtualization
Natural Computing: an international journal
Genetic programming as strategy for learning image descriptor operators
Intelligent Data Analysis
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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.