Range Image Segmentation by Curve Grouping

A range image segmentation method based on a recursive adaptive regression model prediction for detecting range image step discontinuities which are present at object face borders. Detected face borders guides subsequent region growing step where neighbouring face curves are grouped together. Region growing based on curve segments instead of pixels like in classical approaches significantly speed up the algorithm. Curves to be grown are represented using the cubic spline model. Curves from the same region are required to have similar curvature and slope but they do not need to be of maximal length through the corresponding object face.


The structured light (K2T) range image and the intesity image, respectively.
Detected edges and the resulting segmentation.
Haindl, M., and P. Žid, "Range image segmentation by curve grouping", Proceedings of the 7th International Workshop on Robotics in Alpe-Adria-Danube Region, Bratislava, ASCO Art, pp. 339-344, June, 1998.