Abstract
In this paper, the authors propose solutions for finding the vanishing point in real time based on the Random Sample Consensus (RANSAC) curve fitting and density-based spatial clustering of applications with noise (DBSCAN). First, it was proposed to extract the longest segments of lines from the edge frame. Second, a RANSAC curve fitting method was implemented for detecting the best curve fitting given the data set of points for each line segment. Third, the set of intersection points for each pair of curves are extracted. Finally, the DBSCAN method was used in estimating the VP. Preliminary results were gathered and tested on a group of consecutive frames undertaken at Nam-gu, Ulsan, in South Korea. These specific methods of measurement were chosen to prove their effectiveness.
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Cáceres Hernández, D., Hoang, VD., Jo, KH. (2014). Methods for Vanishing Point Estimation by Intersection of Curves from Omnidirectional Image. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8397. Springer, Cham. https://doi.org/10.1007/978-3-319-05476-6_55
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DOI: https://doi.org/10.1007/978-3-319-05476-6_55
Publisher Name: Springer, Cham
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