SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear time-complexity and a squared reconstruction error that decreases at least quadratically, as the number of feature point correspondences increase. Inspired by ideas from triangulation and frame quantisation theory, we define consistent reconstruction and then present SHAPE, our proposed consistent pose estimation algorithm. We compare this algorithm with state-of-the-art pose estimation techniques in terms of accuracy and error decay rate. The experimental results verify our hypothesis on the optimal worst-case quadratic decay and demonstrate its promising performance compared to other approaches.


Published in:
2016 Ieee International Conference On Acoustics, Speech And Signal Processing Proceedings, 1776-1780
Presented at:
41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Shanghai, China, 20-25 March 2016
Year:
2016
Publisher:
New York, Ieee
ISSN:
1520-6149
ISBN:
978-1-4799-9988-0
Keywords:
Laboratories:




 Record created 2016-01-22, last modified 2018-03-17

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