Design of optimal Gaussian operators in small neighbourhoods
Image and Vision Computing
Adaptive multiscale feature extraction from range data
Computer Vision, Graphics, and Image Processing
Computer Vision, Graphics, and Image Processing
Computer Vision and Image Understanding
Simulating facial surgery using finite element models
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
2D-3D Registration Based on Shape Matching
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
A finite element method for surface restoration with smooth boundary conditions
Computer Aided Geometric Design
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - 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
Range image segmentation based on randomized Hough transform
Pattern Recognition Letters
Face^3 a 2D+3D Robust Face Recognition System
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Content-adaptive feature extraction using image variance
Pattern Recognition
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
Coarse-to-fine vision-based localization by indexing scale-Invariant features
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiscale extension of the gravitational approach to edge detection
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Multi-frequency transformation for edge detection
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Multiscale edge detection based on Gaussian smoothing and edge tracking
Knowledge-Based Systems
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Multi-scale feature extraction has become prominent in recent years. Additionally, processing images containing sparse or irregularly distributed data has become increasingly important, in particular with respect to the use of range image data. We present a family of multi-scale gradient-based edge detection algorithms that are suitable for use on either regularly or irregularly distributed image data; these algorithms can be applied directly to the range and intensity images without any image pre-processing. We quantitatively evaluate our algorithms on synthetic intensity and range images and also provide comparative visual output, using real images. The results demonstrate that this approach can be successfully applied to both range and intensity images, providing results that for intensity images are more accurate than from traditional gradient operators and for range images are more accurate than from the scan-line approximation.