@article {397,
	title = {Occupancy mapping and surface reconstruction using local gaussian processes with kinect sensors},
	journal = {Cybernetics, IEEE Transactions on},
	volume = {43},
	number = {5},
	year = {2013},
	pages = {1335-1346},
	keywords = {Bayes methods, Bayesian nonparametric approach, coarse-to-fine clustering method, computational complexity, computational time, computer vision, continuous occupancy mapping, continuous occupancy maps, data visualisation, feature extraction, Gaussian processes, high-computational complexity, high-resolution RGB-D sensors, image colour analysis, image reconstruction, image representation, image sensors, iso-surface extraction, Kinect sensors, local Gaussian processes, map representations, marching cubes, mobile robot navigation, mobile robots, path planning, pattern clustering, RGB-D mapping, robot vision, robotics communities, sensors, SLAM (robots), surface reconstruction, Surface treatment, test data, Training, Training data, visual SLAM},
	isbn = {2168-2267},
	author = {Soohwan, K. and Jonghyuk, K.}
}
