Authors:
Ismail Bozkurt
and
Egemen Özden
Affiliation:
Bahçeşehir University, Turkey
Keyword(s):
3D Registration, Kinect, Local Image Features and Matching.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Geometry and Modeling
;
Image and Video Analysis
;
Image Registration
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
Abstract:
Automatic registration of 3D scans with RGB data is studied in this paper. In contrast to bulk of research in the field which deploy 3D geometry consistency, local RGB image feature matches are used to solve the unknown 3D rigid transformation. The key novelty in this work is the introduction of a new simple measure, we call “Depthscale measure”, which logically represents the size of the local image features in 3D world, thanks to the availability of the depth data from the sensor. Depending on the operating characteristics of the target application, we show this measure can be useful and efficient in eliminating outliers through experimental results. Also system level details are given to help scientists who want to build a similar system.