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Publication - Professor Andrew Calway

    Absolute pose estimation using multiple forms of correspondences from RGB-D frames


    Li, S & Calway, AD, 2016, ‘Absolute pose estimation using multiple forms of correspondences from RGB-D frames’. in: 2016 IEEE International Conference on Robotics and Automation (ICRA 2016): Proceedings of a meeting held 16-21 May 2016, Stockholm, Sweden. Institute of Electrical and Electronics Engineers (IEEE), pp. 4756-4761


    We describe a new approach to absolute pose estimation from noisy and outlier contaminated matching point sets for RGB-D sensors. We show that by integrating multiple forms of correspondence based on 2-D and 3-D points and surface normals gives more precise, accurate and robust pose estimates. This is because it gives more constraints than using one form alone and increases the available measurements, especially when dealing with sparse matching sets. We demonstrate the approach by incorporating it within a RANSAC algorithm and introduce a novel direct least-square approach to calculate pose estimates. Results from experiments on synthetic and real data demonstrate improved performance over existing methods.

    Full details in the University publications repository