A. Chapoulie, P. Rives, D. Filliat. Appearance-based segmentation of indoors/outdoors sequences of spherical views. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'2013, Pages 1946-1951, Tokyo, Japan, November 2013.
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Navigating in large scale, complex and dynamic environments requires reliable representations able to capture metric, topological and semantic aspects of the scene for sup- porting path planing and real time motion control. In a previous work [11], we addressed metric and topological representations thanks to a multi-cameras system which allows building of dense visual maps of large scale 3D environments. The map is a set of locally accurate spherical panoramas related by 6dof poses graph. The work presented here is a further step toward a semantic representation. We aim at detecting the changes in the structural properties of the scene during navigation. Structural properties are estimated online using a global descriptor relying on spherical harmonics which are particularly well-fitted to capture properties in spherical views. A change-point detection algorithm based on a statistical Neyman-Pearson test allows us to find optimal transitions between topological places. Results are presented and discussed both for indoors and outdoors experiments
@InProceedings{Chapoulie13a,
Author = {Chapoulie, A. and Rives, P. and Filliat, D.},
Title = {Appearance-based segmentation of indoors/outdoors sequences of spherical views},
BookTitle = {IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'2013},
Pages = {1946--1951},
Address = {Tokyo, Japan},
Month = {November},
Year = {2013}
}
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