2015 CVPR CVPR 2015

A Metric Parametrization for Trifocal Tensors With Non-Colinear Pinholes

Abstract

The trifocal tensor, which describes the relation between projections of points and lines in three views, is a fundamental entity of geometric computer vision. In this work, we investigate a new parametrization of the trifocal tensor for calibrated cameras with non-colinear pinholes obtained from a quotient Riemannian manifold. We incorporate this formulation into state-of-the art methods for optimization on manifolds, and show, through experiments in pose averaging, that it produces a meaningful way to measure distances between trifocal tensors.

🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — geometric computer vision
🐣 Hot Topic Early Bird — riemannian manifold
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Robotics, Security & Privacy