DiskVPS: Vanishing Point Detector via Hough Transform in a Disk Region
Jianping Wu
摘要
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 equalprobability 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.
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它引用的顶会 Paper8
- Learning to Reconstruct 3D Manhattan Wireframes From a Single ImageYichao Zhou, Haozhi Qi, Yuexiang Zhai, Qi Sun 等ICCV 2019 · 被引用 74 次
- Deep vanishing point detection: Geometric priors make dataset variations vanishYancong Lin, Ruben Wiersma, Silvia L. Pintea, Klaus Hildebrandt 等CVPR 2022 · 被引用 24 次
- Real-time Vanishing Point Detector Integrating Under-parameterized RANSAC and Hough TransformJianping Wu, Liang Zhang, Ye Liu, Ke ChenICCV 2021 · 被引用 17 次
- Transformer Based Line Segment Classifier with Image Context for Real-Time Vanishing Point Detection in Manhattan WorldXin Tong, Xianghua Ying, Yongjie Shi, Ruibin Wang 等CVPR 2022 · 被引用 17 次
- Vanishing Point Estimation in Uncalibrated Images with Prior Gravity DirectionRémi Pautrat, Shaohui Liu, Petr Hruby, Marc Pollefeys 等ICCV 2023 · 被引用 10 次
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