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.
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Ceron, A., Prieto, F. (2013). Evaluating and Comparing of 3D Shape Descriptors for Object Recognition. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_47
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DOI: https://doi.org/10.1007/978-3-642-41939-3_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41938-6
Online ISBN: 978-3-642-41939-3
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