Computer Vision and Image Understanding
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Evaluation of Features Detectors and Descriptors based on 3D Objects
International Journal of Computer Vision
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Faster and Better: A Machine Learning Approach to Corner Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive and generic corner detection based on the accelerated segment test
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Building Rome on a cloudless day
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Coding of Image Feature Descriptors for Distributed Rate-efficient Visual Correspondences
International Journal of Computer Vision
Finding the Best Feature Detector-Descriptor Combination
3DIMPVT '11 Proceedings of the 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission
LDAHash: Improved Matching with Smaller Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Iterative quantization: A procrustean approach to learning binary codes
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Inertial sensor-aligned visual feature descriptors
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
P-SLAM: Simultaneous Localization and Mapping With Environmental-Structure Prediction
IEEE Transactions on Robotics
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
BRISK: Binary Robust invariant scalable keypoints
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Performance evaluation of salient features has a long-standing tradition in computer vision. In this paper, we fill the gap of evaluation for the recent wave of binary feature descriptors, which aim to provide robustness while achieving high computational efficiency. We use established metrics to embed our assessment into the body of existing evaluations, allowing us to provide a novel taxonomy unifying both traditional and novel binary features. Moreover, we analyze the performance of different detector and descriptor pairings, which are often used in practice but have been infrequently analyzed. Additionally, we complement existing datasets with novel data testing for illumination change, pure camera rotation, pure scale change, and the variety present in photo-collections. Our performance analysis clearly demonstrates the power of the new class of features. To benefit the community, we also provide a website for the automatic testing of new description methods using our provided metrics and datasets (www.cs.unc.edu/feature-evaluation).