Abstract— While the most accurate solution to off-line structure from motion (SFM) problems is undoubtedly to extract as much correspondence information as possible and perform g...
Hauke Strasdat, J. M. M. Montiel, Andrew J. Daviso...
Recent work has shown that the probabilistic SLAM approach of explicit uncertainty propagation can succeed in permitting repeatable 3D real-time localization and mapping even in th...
Javier Civera, Andrew J. Davison, J. M. M. Montiel
— This paper presents a method for Simultaneous Localization and Mapping (SLAM), relying on a monocular camera as the only sensor, which is able to build outdoor, closed-loop map...
Laura A. Clemente, Andrew J. Davison, Ian D. Reid,...
Abstract. The ability to localise a camera moving in a previously unknown environment is desirable for a wide range of applications. In computer vision this problem is studied as m...
Abstract. It has recently been demonstrated that the fundamental computer vision problem of structure from motion with a single camera can be tackled using the sequential, probabil...
Javier Civera, Andrew J. Davison, J. M. M. Montiel
We present a monocular SLAM system that avoids inconsistency by coalescing observations into independent local coordinate frames, building a graph of the local frames, and optimiz...
— Recent work has demonstrated the benefits of adopting a fully probabilistic SLAM approach in sequential motion and structure estimation from an image sequence. Unlike standard...
Javier Civera, Andrew J. Davison, J. M. M. Montiel
Monocular SLAM has the potential to turn inexpensive cameras into powerful pose sensors for applications such as robotics and augmented reality. However, current implementations l...
Localization and mapping in unknown environments becomes more difficult as the complexity of the environment increases. With conventional techniques, the cost of maintaining estim...