| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
K. G. Khoo and P. N. Suganthan
ABSTRACT
In this paper, we investigate the genetic algorithm based optimization procedure for structural pattern recognition in a model-based recognition system using attributed relational graph matching technique. In this study, potential solutions indicating the mapping between scene and model vertices are represented by integer strings. The test scene may contain multiple occurrences of different or the same model object. Khoo and Suganthan [Proc. IEEE Congr. Evolutionary Comput. Conf. 2001, p. 727] proposed a solution string representation scheme for multiple mapping between a test scene and all model objects and with the uniform crossover operator. In this paper, we evaluate this proposed solution string representation scheme with another representation scheme commonly used to solve the problem. In addition, a comparison between the uniform, one-point and two-point crossover operators was made. An efficient pose-clustering algorithm is used to eliminate any wrong mappings and to determine the presence/pose of the model in the scene. Simulations are carried out to evaluate the various solution representations and genetic operators. |
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