Vanishing Point Detection Algorithm Based on Clustering Method

Fang Wan; R. Yang

doi:10.4028/www.scientific.net/AMR.846-847.1157

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Vanishing Point Detection Algorithm Based on...

Vanishing Point Detection Algorithm Based on Clustering Method

Abstract:

Camera self-calibration is a key step in photo based reconstruction works. Vanishing point detection is a very important method in single photo based camera self-calibration. We research current vanishing point detection method and put forward a detection algorithm based on a new clustering idea: J-Linkage. First, we construct a similar concept space from straight lines from images by edge detection and segmentation method. Then, we cluster the similar concept space to decide several main directions. At last, we can easily estimate vanishing points from the clustered categories. Experiment prove that, the method has a high performance efficiency and with good accuracy.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1157-1161

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1157

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Online since:

November 2013

Authors:

Fang Wan*, R. Yang

Keywords:

Clustering, J-Linkage, Self-Calibration, Vanishing Point

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