This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Stochastic tracking of structured models in monolithic state spaces often requires modeling complex distributions that are difficult to represent with either parametric or sample...
Leonid Taycher, John W. Fisher III, Trevor Darrell
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
This paper presents a vision-based approach to SLAM in indoor / outdoor environments with minimalistic sensing and computational requirements. The approach is based on a graph repr...
Henrik Andreasson, Tom Duckett, Achim J. Lilientha...