Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion. II
SIAM Journal on Numerical Analysis
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Canonical Frames for Planar Object Recognition
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Affine/ Photometric Invariants for Planar Intensity Patterns
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Geometrical PDEs based on second-order derivatives of gauge coordinates in image processing
Image and Vision Computing
SAR Image Matching Based on Speeded Up Robust Feature
GCIS '09 Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04
Flow separation for fast and robust stereo odometry
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Discriminative Learning of Local Image Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Top-points as interest points for image matching
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words
IEEE Transactions on Robotics
An axiomatic approach to image interpolation
IEEE Transactions on Image Processing
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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In this paper, we present a novel family of multiscale local feature descriptors, a theoretically and intuitively well justified variant of SURF which is straightforward to implement but which nevertheless is capable of demonstrably better performance with comparable computational cost. Our family of descriptors, called Gauge-SURF (G-SURF), is based on second-order multiscale gauge derivatives. While the standard derivatives used to build a SURF descriptor are all relative to a single chosen orientation, gauge derivatives are evaluated relative to the gradient direction at every pixel. Like standard SURF descriptors, G-SURF descriptors are fast to compute due to the use of integral images, but have extra matching robustness due to the extra invariance offered by gauge derivatives. We present extensive experimental image matching results on the Mikolajczyk and Schmid dataset which show the clear advantages of our family of descriptors against first-order local derivatives based descriptors such as: SURF, Modified-SURF (M-SURF) and SIFT, in both standard and upright forms. In addition, we also show experimental results on large-scale 3D Structure from Motion (SfM) and visual categorization applications.