Relative Pose Estimation from Straight Lines Using Optical Flow-Based Line Matching and Parallel Line Clustering
| Autor: | Pierre Lothe, Naja von Schmude, Bernd Jähne, Jonas Witt |
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| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Communications in Computer and Information Science ISBN: 9783319648699 VISIGRAPP (Revised Selected Papers) |
| DOI: | 10.1007/978-3-319-64870-5_16 |
| Popis: | This paper tackles the problem of relative pose estimation between two monocular camera images in textureless scenes. Due to a lack of point matches, point-based approaches such as the 5-point algorithm often fail when used in these scenarios. Therefore we investigate relative pose estimation from line observations. We propose a new algorithm in which the relative pose estimation from lines is extended by a 3D line direction estimation step. Using the estimated line directions, the robustness and computational efficiency of the relative pose calculation is greatly improved. Furthermore, we investigate line matching techniques as the quality of the matches influences directly the outcome of the relative pose estimation. We develop a novel line matching strategy for small baseline matching based on optical flow which outperforms current state-of-the-art descriptor-based line matchers. First, we describe in detail the proposed line matching approach. Second, we introduce our relative pose estimation based on 3D line directions. We evaluate the different algorithms on synthetic and real sequences and demonstrate that in the targeted scenarios we outperform the state-of-the-art in both accuracy and computation time. |
| Databáze: | OpenAIRE |
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