BRIEF: Computing a Local Binary Descriptor Very Fast

Binary descriptors are becoming increasingly popular as a means to compare feature points very fast while requiring comparatively small amounts of memory. The typical approach to creating them is to first compute floating-point ones, using an algorithm such as SIFT, and then to binarize them. In this paper, we show that we can directly compute a binary descriptor, which we call BRIEF, on the basis of simple intensity difference tests. As a result, BRIEF is very fast both to build and to match. We compare it against SURF and SIFT on standard benchmarks and show that it yields comparable recognition accuracy, while running in an almost vanishing fraction of the time required by either.

[1]  Tony Lindeberg,et al.  Scale-Space for Discrete Signals , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Ramin Zabih,et al.  Non-parametric Local Transforms for Computing Visual Correspondence , 1994, ECCV.

[3]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[4]  Piotr Indyk,et al.  Similarity Search in High Dimensions via Hashing , 1999, VLDB.

[5]  Trevor Darrell,et al.  Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[6]  Andreas Ernst,et al.  Face detection with the modified census transform , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[7]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[8]  J. Koenderink The structure of images , 2004, Biological Cybernetics.

[9]  Fridtjof Stein,et al.  Efficient Computation of Optical Flow Using the Census Transform , 2004, DAGM-Symposium.

[10]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.

[11]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Gregory Shakhnarovich,et al.  Learning task-specific similarity , 2005 .

[13]  Vincent Lepetit,et al.  Keypoint recognition using randomized trees , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[15]  Tom Drummond,et al.  Machine Learning for High-Speed Corner Detection , 2006, ECCV.

[16]  Matti Pietikäinen,et al.  Local Binary Pattern Descriptors for Dynamic Texture Recognition , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[17]  Gang Hua,et al.  Discriminant Embedding for Local Image Descriptors , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[18]  Cordelia Schmid,et al.  Vector Quantizing Feature Space with a Regular Lattice , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[19]  Vincent Lepetit,et al.  Fast Keypoint Recognition in Ten Lines of Code , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Sébastien Marcel,et al.  On the Recent Use of Local Binary Patterns for Face Authentication , 2007 .

[21]  Geoffrey E. Hinton,et al.  Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure , 2007, AISTATS.

[22]  A. Vedaldi An open implementation of the SIFT detector and descriptor , 2007 .

[23]  Kurt Konolige,et al.  CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching , 2008, ECCV.

[24]  Dieter Schmalstieg,et al.  Pose tracking from natural features on mobile phones , 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

[25]  Antonio Torralba,et al.  Small codes and large image databases for recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[26]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[27]  Pascal Fua,et al.  On benchmarking camera calibration and multi-view stereo for high resolution imagery , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[28]  Loris Nanni,et al.  Local binary patterns for a hybrid fingerprint matcher , 2008, Pattern Recognit..

[29]  Marko Heikkilä,et al.  Description of interest regions with local binary patterns , 2009, Pattern Recognit..

[30]  Tom Drummond,et al.  Robust feature matching in 2.3µs , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[31]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[32]  Loris Nanni,et al.  High Performance Set of Features for Human Action Classification , 2009, IPCV.

[33]  Matthew A. Brown,et al.  Picking the best DAISY , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[34]  Vincent Lepetit,et al.  Compact signatures for high-speed interest point description and matching , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[35]  Shuicheng Yan,et al.  An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[36]  Cordelia Schmid,et al.  Improving Bag-of-Features for Large Scale Image Search , 2010, International Journal of Computer Vision.

[37]  Vincent Lepetit,et al.  Fast Keypoint Recognition Using Random Ferns , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[38]  Vincent Lepetit,et al.  DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[39]  Tom Drummond,et al.  Faster and Better: A Machine Learning Approach to Corner Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[40]  Cordelia Schmid,et al.  Product Quantization for Nearest Neighbor Search , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[41]  Gang Hua,et al.  Discriminative Learning of Local Image Descriptors , 1990, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[42]  Pascal Fua,et al.  LDAHash: Improved Matching with Smaller Descriptors , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.