期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2015
卷号：XL-5/W6
页码：107-111
DOI：10.5194/isprsarchives-XL-5-W6-107-2015
出版社：Copernicus Publications
摘要：The paper presents an original method for object detection. The “texture” Hough transform is used as the main tool in the search. Unlike classical generalized Hough transform, this variation uses texture LBP descriptor as a primitive for voting. The voting weight of each primitive is assumed by learning at a training set. This paper gives an overview of an original method for weights learning, and a number of ways to get the maximum searching algorithm speed on practice
关键词：Local Binary Pattern; Object detection; facial features detection; Hough transform
