Vanishing points detection using combination of fast hough transform and deep learning

被引:12
|
作者
Sheshkus, Alexander [1 ]
Ingacheva, Anastasia [2 ]
Nikolaev, Dmitry [2 ]
机构
[1] Smart Engines, Moscow, Russia
[2] RAS, Kharkevich Inst, Inst Informat Transmiss Problems, Moscow, Russia
基金
俄罗斯基础研究基金会;
关键词
Fast Hough Transform; vanishing points; deep learning; convolutional neural network;
D O I
10.1117/12.2310170
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we propose a novel method for vanishing points detection based on convolutional neural network (CNN) approach and Fast Hough transform algorithm. We show how to determine Fast Hough Transform neural network layer and how to use it in order to increase usability of the neural network approach to the vanishing point detection task. Our algorithm includes CNN with consequence of convolutional and fast Hough transform layers. We are building estimator for distribution of possible vanishing points in the image. This distribution can be used to find candidates of vanishing point. We provide experimental results from tests of suggested method using images collected from videos of a road trips. Our approach shows stable result on test images with different projective distortions and noise. Described approach can be effectively implemented for mobile GPU and CPU.
引用
收藏
页数:8
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