2013 | OriginalPaper | Buchkapitel
A Genetic Algorithm-Evolved 3D Point Cloud Descriptor
verfasst von : Dominik Węgrzyn, Luís A. Alexandre
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer Berlin Heidelberg
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In this paper we propose a new descriptor for 3D point clouds that is fast when compared to others with similar performance and its parameters are set using a genetic algorithm. The idea is to obtain a descriptor that can be used in simple computational devices, that have no GPUs or high computational capabilities and also avoid the usual time-consuming task of determining the optimal parameters for the descriptor. Our proposal is compared with other similar algorithms in a public available point cloud library (PCL [1]). We perform a comparative evaluation on 3D point clouds using both the object and category recognition performance. Our proposal presents a comparable performance with other similar algorithms but is much faster and requires less disk space.