Abstract
Efficient and compact representation of local image patches in the form of features descriptors that are distinctive/robust as well as fast to compute and match is an essential and inevitable step for many computer vision applications. One category of these representations is the binary descriptors which have been shown to be successful alternatives providing similar performance to their floating-point counterparts while being efficient to compute and store. In this paper, a comprehensive performance evaluation of the current state-of-the-art binary descriptors; namely, BRIEF, ORB, BRISK, FREAK, and LATCH is presented in the context of image matching. This performance evaluation highlights several points regarding the performance characteristics of binary descriptors under various geometric and photometric transformations of images.
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Awad, A.I., Hassaballah, M.: Image feature detectors and descriptors: foundations and applications. In: Studies in computational intelligence (ISSN 1860-949X), vol. 630. Springer (2016)
Tuytelaars, T., Mikolajczyk, K.: Local invariant feature detectors: a survey. Found. Trends Comput. Graph. Vis. 3(3), 177–280 (2008)
Hassaballah, M., Aly, A.A., Alshazly, H.A.: Image features detection, description and matching. In: Image Feature Detectors and Descriptors: Foundations and Applications, vol. 630, pp. 11–45. Springer (2016)
Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Bay, H., Ess, A., Tuytelaars, T., Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Heinly, J., Dunn, E., Frahm, J.M.: Comparative evaluation of binary features. In: European Conference on Computer Vision, pp. 759–773. Florence, Italy (2012)
Bekele, D., Teutsch, M., Schuchert, T.: Evaluation of binary keypoint descriptors. In: IEEE International Conference on Image Processing, Melbourne, Australia, pp. 3652–3656 (2013)
Figat, J., Kornuta, T., Kasprzak, W.: Performance evaluation of binary descriptors of local features. In: International Conference on Computer Vision and Graphics, Warsaw, Poland, pp. 187–194 (2014)
Mukherjee, D., Wu, Q.J., Wang, G.: A comparative experimental study of image feature detectors and descriptors. Mach. Vis. Appl. 26(4), 443–466 (2015)
Johansson, J., Solli, M., Maki, A.: An evaluation of local feature detectors and descriptors for infrared images. In: European Conference on Computer Vision Workshops, Amsterdam, The Netherlands, pp. 711–723 (2016)
Calonder, M., Lepetit, V., Ozuysal, M., Trzcinski, T., Strecha, C., Fua, P.: Brief: computing a local binary descriptor very fast. IEEE Trans. Pattern Anal. Mach. Intell. 34(7), 1281–1298 (2012)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to sift or surf. In: ICCV, Barcelona, Spain, pp. 2564–2571 (2011)
Rosten, E., Porter, R., Drummond, T.: Faster and better: a machine learning approach to corner detection. IEEE Trans. Pattern Anal. Mach. Intell. 32(1), 105–119 (2010)
Leutenegger, S., Chli, M., Siegwart, R.Y.: BRISK: binary robust invariant scalable keypoints. In: ICCV, Barcelona, Spain, pp. 2548–2555 (2011)
Mair, E., Hager, G.D., Burschka, D., Suppa, M., Hirzinger, G.: Adaptive and generic corner detection based on the accelerated segment test. In: European Conference on Computer Vision, Crete, Greece, pp. 183–196 (2010)
Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK: fast retina keypoint. In: IEEE Conference on Computer Vision and Pattern Recognition, Rhode Island, USA, pp. 510–517 (2012)
Levi, G., Hassner, T.: LATCH: learned arrangements of three patch codes. In: IEEE Winter Conference on Applications of Computer Vision, NY, USA, pp. 1–9 (2016)
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Alshazly, H.A., Hassaballah, M., Ali, A.A., Wang, G. (2018). An Experimental Evaluation of Binary Feature Descriptors. In: Hassanien, A., Shaalan, K., Gaber, T., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017. AISI 2017. Advances in Intelligent Systems and Computing, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-64861-3_17
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DOI: https://doi.org/10.1007/978-3-319-64861-3_17
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