Abstract
This paper presents a comparison of the different colour spaces used in an environment modelling algorithm. This algorithm is based on the fusion of depth and colour information of a low-cost RGB-D camera to model an indoor environment. This modelling is based on creating and updating Gaussian models of the colour of the walkable floor. The analysis carried out tests the performance of three different colour spaces, obtaining the best choice to get a correct floor segmentation and reconstruction. As the results show, the algorithm performance highly depends on the colour space chosen. The method has been evaluated in a set of frames representing different environments captured with a RGB-D camera.
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Pardeiro, J., Gómez, J.V., Álvarez, D., Moreno, L. (2014). Learning-Based Floor Segmentation and Reconstruction. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-319-03653-3_23
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DOI: https://doi.org/10.1007/978-3-319-03653-3_23
Publisher Name: Springer, Cham
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