DocumentCode :
253633
Title :
Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains
Author :
Lezama, Jose ; Grompone von Gioi, Rafael ; Randall, Gregory ; Morel, Jean-Michel
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
509
Lastpage :
515
Abstract :
We present a novel method for automatic vanishing point detection based on primal and dual point alignment detection. The very same point alignment detection algorithm is used twice: First in the image domain to group line segment endpoints into more precise lines. Second, it is used in the dual domain where converging lines become aligned points. The use of the recently introduced PClines dual spaces and a robust point alignment detector leads to a very accurate algorithm. Experimental results on two public standard datasets show that our method significantly advances the state-of-the-art in the Manhattan world scenario, while producing state-of-the-art performances in non-Manhattan scenes.
Keywords :
object detection; Manhattan world scenario; PClines dual spaces; automatic vanishing point detection; dual domains; dual point alignment detection; group line segment endpoints; image primal domains; nonManhattan scenes; public standard datasets; Cameras; Clustering algorithms; Detectors; Estimation; Image segmentation; Three-dimensional displays; Transforms; 2d point alignments; line-to-point mapping; vanishing point detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPR.2014.72
Filename :
6909466
Link To Document :
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