2013 ICCV ICCV 2013

Video Motion for Every Visible Point

Abstract

Dense motion of image points over many video frames can provide important information about the world. However, occlusions and drift make it impossible to compute long motion paths by merely concatenating optical flow vectors between consecutive frames. Instead, we solve for entire paths directly, and flag the frames in which each is visible. As in previous work, we anchor each path to a unique pixel which guarantees an even spatial distribution of paths. Unlike earlier methods, we allow paths to be anchored in any frame. By explicitly requiring that at least one visible path passes within a small neighborhood of every pixel, we guarantee complete coverage of all visible points in all frames. We achieve state-of-the-art results on real sequences including both rigid and non-rigid motions with significant occlusions.

🚀 Conference Pioneer — ICCV 2013
🧭 Keyword Pioneer — video motion
🐣 Hot Topic Early Bird — motion estimation
🐝 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