Understanding 3D shapes being in motion

• Autorzy: Bedkowski J.
• Języki publikacji: EN

Abstrakty

EN

This paper concerns a classification problem of 3D shapes being in motion. The goal is to develop the system with real-time capabilities to distinguish basic shapes (corners, planes, cones, spheres etc.) that are moving in front of RGB-D sensor. It is introduced an improvement of SoA algorithms (normal vector computation using PCA Principal Component Analysis and SVD Singular Value Decomposition, PFH – Point Feature Histogram) based on GPGPU (General Purpose Graphic Processor Unit) computation. This approach guarantee on-line computation of normal vectors, unfortunately computation time of the PFH for each normal vector is still a challenge to obtain on-line capabilities, therefore in this paper it is shown how to find a region of movement and to perform the classification process assuming the decreased amount of data. Proposed approach can be a starting point for further developments of the systems able to recognize the objects in the dynamic environments.

Słowa kluczowe

EN

RGB-D camera; point cloud; normal vector estimation; point feature histogram; parallel programming

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2013
• Tom: Vol. 7, No. 1
• Strony: 42--46
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Bedkowski J.

• Intitute of Mathematical Machines, Institute of Automation and Robotics, Warsaw, Poland

Bibliografia

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