Abstract

A feature detector and a feature descriptor are presented, which are applicable to 3D range data. The feature detector is used to identify locations in the range data at which the feature descriptor is applied. The feature descriptor, or feature transform, calculates a signature for each identified location on the basis of local shape information. The approach used in both the feature detector and the descriptor is motivated by the success of the scale invariant feature transform and speeded up robust features approaches in the 2D case. Using synthetic data, the authors evaluate the repeatability of the detector and robustness of the descriptor to global transformations and image noise. The complete system is then applied to the problem of automatic detection of repeated structure in real range images.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.