title: Occupancy mapping and surface reconstruction using local Gaussian processes with Kinect sensors.
abstract: Although RGB-D sensors have been successfully applied to visual SLAM and surface reconstruction, most of the applications aim at visualization. In this paper, we propose a noble method of building continuous occupancy maps and reconstructing surfaces in a single framework for both navigation and visualization. Particularly, we apply a Bayesian nonparametric approach, Gaussian process classification, to occupancy mapping. However, it suffers from high-computational complexity of O(n(3))+O(n(2)m), where n and m are the numbers of training and test data, respectively, limiting its use for large-scale mapping with huge training data, which is common with high-resolution RGB-D sensors. Therefore, we partition both training and test data with a coarse-to-fine clustering method and apply Gaussian processes to each local clusters. In addition, we consider Gaussian processes as implicit functions, and thus extract iso-surfaces from the scalar fields, continuous occupancy maps, using marching cubes. By doing that, we are able to build two types of map representations within a single framework of Gaussian processes. Experimental results with 2-D simulated data show that the accuracy of our approximated method is comparable to previous work, while the computational time is dramatically reduced. We also demonstrate our method with 3-D real data to show its feasibility in large-scale environments.
authors.forename: Soohwan
authors.initials: S
authors.lastname: Kim
authors.forename: Jonghyuk
authors.initials: J
authors.lastname: Kim
mesh_terms: D056044:Actigraphy / Q000295:instrumentation / Q000379:methods; D000465:Algorithms; D001185:Artificial Intelligence; D016287:Computer Peripherals; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D014159:Transducers; D018910:Video Games; D051598:Whole Body Imaging / Q000295:instrumentation / Q000379:methods*