DP-Fusion: A generic framework for online multi sensor recognition
Ming Liu, Lujia Wang, Roland Siegwart · 2012
Multi sensor fusion has been widely used in recognition problems. Most existing works highly depend on the calibration between different sensors, but less on modeling and reasoning of the co-incidence of multiple hints. In this paper, we propose a generic framework for recognition and clustering problem using a non-parametric Dirichlet hierarchical model, named DP-Fusion. It enables online labeling, clustering and recognition of sequential data simultaneously, while considering multiple types of sensor readings. The algorithm is data-driven, which does not depend on priorknowledge of the data structure. The results show the feasibility and reliability against noise data.