Title :
DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera
Author :
Liu, Ming ; Siegwart, Roland
Author_Institution :
Autonomous Syst. Lab., ETH Zurich, Zurich, Switzerland
Abstract :
Topological mapping and scene recognition problems are still challenging, especially for online realtime vision-based applications. We develop a hierarchical probabilistic model to tackle them using color information. This work is stimulated by our previous work [1] which defined a lightweight descriptor using color and geometry information from segmented panoramic images. Our novel model uses a Dirichlet Process Mixture Model to combine color and geometry features which are extracted from omnidirectional images. The inference of the model is based on an approximation of conditional probabilities of observations given estimated models. It allows online inference of the mixture model in real-time (at 50Hz), which outperforms other existing approaches. A real experiment is carried out on a mobile robot equipped with an omnidirectional camera. The results show the competence against the state-of-art.
Keywords :
approximation theory; computational geometry; image colour analysis; image segmentation; image sensors; inference mechanisms; mobile robots; object recognition; probability; robot vision; stochastic processes; DP-FACT; Dirichlet process mixture model; color information; conditional probability approximation; geometry information; hierarchical probabilistic model; mobile robot; omnidirectional camera; online inference; online realtime vision-based applications; panoramic image segmentation; scene recognition problem; topological mapping problem; Current measurement; Equations; Histograms; History; Image color analysis; Mathematical model; Real time systems;
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
DOI :
10.1109/ICRA.2012.6225040