2013 CVPR CVPR 2013

A Global Approach for the Detection of Vanishing Points and Mutually Orthogonal Vanishing Directions

Abstract

This article presents a new global approach for detecting vanishing points and groups of mutually orthogonal vanishing directions using lines detected in images of man-made environments. These two multi-model fitting problems are respectively cast as Uncapacited Facility Location (UFL) and Hierarchical Facility Location (HFL) instances that are efficiently solved using a message passing inference algorithm. We also propose new functions for measuring the consistency between an edge and a putative vanishing point, and for computing the vanishing point defined by a subset of edges. Extensive experiments in both synthetic and real images show that our algorithms outperform the state-ofthe-art methods while keeping computation tractable. In addition, we show for the first time results in simultaneously detecting multiple Manhattan-world configurations that can either share one vanishing direction (Atlanta world) or be completely independent.

🚀 Conference Pioneer — CVPR 2013
🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — hierarchical facility location
🐣 Hot Topic Early Bird — 3d vision
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio