Adding rotational robustness to the Surface-Approximation Polynomials descriptor | Zendy

Richard Bormann | Zendy; Jan Fischer | Zendy; Georg Arbeiter | Zendy; Alexander Verl | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Adding rotational robustness to the Surface-Approximation Polynomials descriptor

Author(s) -

Richard Bormann,

Jan Fischer,

Georg Arbeiter,

Alexander Verl

Publication year - 2012

Publication title -

fraunhofer-publica (fraunhofer-gesellschaft)

Language(s) - English

Resource type - Conference proceedings

ISSN - 2164-0572

DOI - 10.1109/humanoids.2012.6651552

Subject(s) - robustness (evolution) , artificial intelligence , computer vision , computation , invariant (physics) , computer science , point cloud , categorization , surface (topology) , mathematics , algorithm , geometry , biochemistry , chemistry , mathematical physics , gene

The Surface-Approximation Polynomials (SAP) descriptor has been shown to be an appropriate global surface edscriptor for object categorization tasks in robotic applications. Nevertheless, in the original formulation the SAP descriptor is not invariant against rotations around the camera axis. This paper explains and evaluates two methods which pre-process the input data to yield repeatably well-aligned point clouds for the cimputation of the SAP descriptor. Whe show that the SAP descriptor can be rendered robust against rotations while retaining almost the full performance of the original approach which is superior to GFPFH, GRSD and VFH

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research