Design of optimal Gaussian operators in small neighbourhoods
Image and Vision Computing
Active, optical range imaging sensors
Machine Vision and Applications
Computer Vision, Graphics, and Image Processing
Surface correspondence and motion computation from a pair of range images
Computer Vision and Image Understanding
Integrating range and object data for robot navigation
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
Robust Segmentation of Primitives from Range Data in the Presence of Geometric Degeneracy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge-Region-Based Segmentation of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Device Space Design for Efficient Scale-Space Edge Detection
ICCS '02 Proceedings of the International Conference on Computational Science-Part I
2D-3D Registration Based on Shape Matching
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
A fast multi-scale edge detection algorithm
Pattern Recognition Letters
Edge Detection in Range Images of Piled Box-like Objects
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Results on Range Image Segmentation for Service Robots
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
A 3D image processing method for manufacturing process automation
Computers in Industry - Special issue: Machine vision
Face^3 a 2D+3D Robust Face Recognition System
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Integration of 2D and 3D images for enhanced face authentication
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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In recent years range images have become prominent in computer vision applications as they provide an almost 3-D description of an otherwise 2-D scene and are suitable for computer vision tasks such as localisation and navigation. Feature extraction from range images has proven to be a complex problem; developing operators that can characterise features in a range image, such as step, crease, or smooth edges, is challenging, due to both the irregular spatial distribution of range image data and the nature of the features themselves. We present an adaptive design procedure for first order gradient operators that can automatically change shape to accommodate irregular data distribution; through appropriate analysis of the output responses, we show that the operators can also be specialised to characterise particular types of range image features. Hence the method is appropriate for direct use on range image data without re-sampling.