We propose a novel method for automatically discover-ing key motion patterns happening in a scene by observing the scene for an extended period. Our method does not rely on object ...
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...
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Most vision-based UAV (Unmanned Aerial Vehicle) navigation algorithms extract manmade features such as buildings or roads, which are well structured in urban terrain, using the CC...
Jihwan Woo, Kilho Son, Teng Li, Gwan Sung Kim, In-...
This paper presents a markerless tracking technique targeted to the Windows Mobile Pocket PC platform. The primary aim of this work is to allow the development of standalone augme...