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

Alexander Sheshkus; Anastasia Ingacheva; Dmitry Nikolaev

doi:10.1117/12.2310170

13 April 2018 Vanishing points detection using combination of fast Hough transform and deep learning

Alexander Sheshkus, Anastasia Ingacheva, Dmitry Nikolaev

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106960H (2018) https://doi.org/10.1117/12.2310170
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

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 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.

Citation Download Citation

Alexander Sheshkus, Anastasia Ingacheva, and Dmitry Nikolaev "Vanishing points detection using combination of fast Hough transform and deep learning", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960H (13 April 2018); https://doi.org/10.1117/12.2310170

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