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http://dx.doi.org/10.9708/jksci.2013.18.9.053

The Method of Vanishing Point Estimation in Natural Environment using RANSAC  

Weon, Sun-Hee (Dept. of Global Media, Soongsil University)
Joo, Sung-Il (Dept. of Global Media, Soongsil University)
Choi, Hyung-Il (Dept. of Global Media, Soongsil University)
Publication Information
Journal of the Korea Society of Computer and Information / v.18, no.9, 2013 , pp. 53-62 More about this Journal
Abstract
This paper proposes a method of automatically predicting the vanishing point for the purpose of detecting the road region from natural images. The proposed method stably detects the vanishing point in the road environment by analyzing the dominant orientation of the image and predicting the vanishing point to be at the position where the feature components of the image are concentrated. For this purpose, in the first stage, the image is partitioned into sub-blocks, an edge sample is selected randomly from within the sub-block, and RANSAC is applied for line fitting in order to analyze the dominant orientation of each sub-block. Once the dominant orientation has been detected for all blocks, we proceed to the second stage and randomly select line samples and apply RANSAC to perform the fitting of the intersection point, then measure the cost of the intersection model arising from each line and we predict the vanishing point to be located at the average point, based on the intersection point model with the highest cost. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for detecting the vanishing point.
Keywords
RANSAC; Vanishing point estimation; Dominant orientation detection; Road detection;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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