Vehicle detection using PLS Hough transform
Frontiers of Computer Vision（2015）
摘要
This paper proposes extended Generalized Hough Transform (GHT) to introduce training process by using Partial Least Squares (PLS) regression analysis. Hough transform can robustly detect patterns against noise and occlusions, and GHT is adapted to perform the generic object detection. In this study, we introduced training process to determine the voting weight of GHT by using PLS regression analysis. Thereby, it becomes possible to generic object detection, while maintaining the framework of Hough-based object detection. In this paper, we applied PLS Hough transform to the vehicle detection from satellite images. In addition, we compared PLS Hough transform with the previous approach (original GHT) on the vehicle detection, and our proposed method achieved high detection accuracy.
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关键词
hough transforms,geophysical image processing,least squares approximations,object detection,regression analysis,road vehicles,ght,hough-based object detection,pls hough transform,pls regression analysis,generalized hough transform,generic object detection,noise,occlusions,partial least squares regression analysis,patterns detection,satellite images,training process,vehicle detection,voting weight,pls regression,feature extraction,shape,data models
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