Abstract--Boosting covariance data on Riemannian manifolds has proven to be a convenient strategy in a pedestrian detection context. In this paper we show that the detection perfor...
Diego Tosato, Michela Farenzena, Marco Cristani, V...
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
— This paper studies the effects of the geometry of a mobile robot formation on the accuracy of the robots’ localization. The general case of heterogeneous (in terms of sensor ...
Yukikazu S. Hidaka, Anastasios I. Mourikis, Stergi...
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
We consider direct sequence code division multiple access (DS-CDMA), modeling interference from users communicating with neighboring base stations by additive colored noise. We con...