Recognition systems attempt to recover information about the identity of observed objects and their location in the environment. A fundamental problem in recognition is pose estima...
Abstract—This paper presents a probabilistic algorithm for simultaneously estimating the pose of a mobile robot and the positions of nearby people in a previously mapped environm...
Michael Montemerlo, Sebastian Thrun, William Whitt...
— This work deals with a group of mobile sensors sampling a spatiotemporal random field whose mean is unknown and covariance is known up to a scaling parameter. The Bayesian pos...
We present a human-centric paradigm for scene understanding. Our approach goes beyond estimating 3D scene geometry and predicts the “workspace” of a human which is represented...
Abhinav Gupta, Scott Satkin, Alyosha Efros, Martia...
Abstract--Positioning in indoor wireless environments is growing rapidly in importance and gains commercial interests in context-awareness applications. The essential challenge in ...