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Publication - Professor Walterio Mayol-Cuevas

    Real-Time and Robust Monocular SLAM Using Predictive Multi-resolution Descriptors

    Citation

    Chekhlov, D, Pupilli, M, Mayol-Cuevas, W & Calway, A, 2006, ‘Real-Time and Robust Monocular SLAM Using Predictive Multi-resolution Descriptors’. in: 2nd International Symposium on Visual Computing.

    Abstract

    We describe a robust system for vision-based SLAM using a single
    camera which runs in real-time, typically around 30 fps. The key
    contribution is a novel utilisation of multi-resolution descriptors in
    a coherent top-down framework. The resulting system provides superior
    performance over previous methods in terms of robustness to erratic
    motion, camera shake, and the ability to recover from measurement
    loss. SLAM itself is implemented within an unscented Kalman filter
    framework based on a constant position motion model, which is also
    shown to provide further resilience to non-smooth camera
    motion. Results are presented illustrating successful SLAM operation
    for challenging hand-held camera movement within desktop
    environments.





    Full details in the University publications repository