Local binary patterns: Difference between revisions

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Previous content was an overstatement, see http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/
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'''Local binary patterns''' (LBP) is a type of feature used for classification in [[computer vision]]. LBP was first described in 1994.<ref>T. Ojala, M. Pietikäinen, and D. Harwood (1994), "Performance evaluation of texture measures with classification based on Kullback discrimination of distributions", Proceedings of the 12th IAPR International Conference on Pattern Recognition (ICPR 1994), vol. 1, pp. 582 - 585.</ref><ref>T. Ojala, M. Pietikäinen, and D. Harwood (1996), "A Comparative Study of Texture Measures with Classification Based on Feature Distributions", Pattern Recognition, vol. 29, pp. 51-59.</ref> It has since been found to be a powerful feature for texture classification; it has further been determined that when LBP is combined with the [[Histogram of oriented gradients]] (HOG) classifier, it yieldsimproves the bestdetection classifierperformance ofconsidarably humanson (i.e.some person vs. non-person) among the classifiers usually considered in academic literaturedatasets<ref>"An HOG-LBP Human Detector with Partial Occlusion Handling", Xiaoyu Wang, Tony X. Han, Shuicheng Yan, ICCV 2009</ref>.
 
==Concept==