Abstract
In this work we show the results of a system for object recognition by using depth data. It is based on shape descriptors and PCA reduction. For obtaining the results, we evaluated different combination of three descriptors that are suitable for this work: Spin Images, VFH (Viewpoint Feature Histogram) and NARF (Normal Aligned Radial Feature). In addition, we created a method for extracting the NARF descriptor in order to obtain a global descriptor. The results show that the combination of descriptors can be used for object recognition in a database composed of point clouds obtained with a RGB-D sensor. © 2013 Springer-Verlag.
Cite
CITATION STYLE
Ceron, A., & Prieto, F. (2013). Evaluating and comparing of 3D shape descriptors for object recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8034 LNCS, pp. 484–492). https://doi.org/10.1007/978-3-642-41939-3_47
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
