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