In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
This paper addresses the problem of seeking out parts of the environment that provide adequate features in order to perform robot localization. The objective is to choose good regi...
— In this paper we describe an approach to feature representation for simultaneous localization and mapping, SLAM. It is a general representation for features that addresses symm...
John Folkesson, Patric Jensfelt, Henrik I. Christe...
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
— This paper introduces a localization based on GPS and laser measurements for urban and non-urban outdoor environments. In this approach, the GPS pose is Kalman filtered using w...