DiskVPS: Vanishing Point Detector via Hough Transform in a Disk Region

Abstract

DiskVPS is a novel and robust vanishing point (VP) detection scheme based on Hough Transform (HT) over an image-plane-mapped disk region. In the DiskVPS, the image plane is first mapped into a disk region, which is then partitioned into concentrical ring-shaped subspaces. Each subspace is further partitioned into approximately equal-probability Hough cells. By using individual edges rather than edge pairs as voters, DiskVPS can achieve high accuracy with extreme efficiency. Involving no calibration parameters, DiskVPS is particularly suitable for VP detection in uncalibrated images and thus can be applied in image calibration. A comparative experimental study demonstrates that the basic DiskVPS model without parameter optimization achieved significantly better performance over the SOTA in detection accuracy and processing speed with real-world images. The study also shows that DiskVPS is robust against parameter changes.