Abstract
There are a lot of three-dimensional reconstruction applications of real scenes. The rise of low-cost sensors, like the Microsoft Kinect, suggests the development of systems cheaper than the existing ones. Nevertheless, data provided by this device are worse than that provided by more sophisticated sensors. In the academic and commercial world, some initiatives try to solve that problem. Studying that attempts, this work suggests the modification of super-resolution algorithm described by Mitzel et al. [1] in order to consider in its calculations colored images provided by Kinect. This change improved the super-resolved depth maps provided, mitigating interference caused by sudden changes of captured scenes. The tests showed the improvement of generated maps and analysed the impact of CPU and GPU algorithms implementation in the super-resolution step.
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dos Santos, L.T.A., Loaiza Fernandez, M.E., Raposo, A.B. (2014). Generating Super-Resolved Depth Maps Using Low-Cost Sensors and RGB Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_61
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DOI: https://doi.org/10.1007/978-3-319-14364-4_61
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