Navigating, Recognizing and Describing Urban Spaces With Vision and Lasers
International Journal of Robotics Research
Visual tracking of planes with an uncalibrated central catadioptric camera
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Vast-scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment
International Journal of Robotics Research
Real-time spherical mosaicing using whole image alignment
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo
International Journal of Computer Vision
Tracking planes with large interframe displacement by fusing template and point based approaches
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
Stereo camera based wearable reading device
AH '12 Proceedings of the 3rd Augmented Human International Conference
Fusing template and point information to track planes with large interframe displacement
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
Photogeometric Direct Visual Tracking for Central Omnidirectional Cameras
Journal of Mathematical Imaging and Vision
Experience-based navigation for long-term localisation
International Journal of Robotics Research
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This paper addresses the problem of motion estimation and 3-D reconstruction through visual tracking with a single-viewpoint sensor and, in particular, how to generalize tracking to calibrated omnidirectional cameras. We analyze different minimization approaches for the intensity-based cost function (sum of squared differences). In particular, we propose novel variants of the efficient second-order minimization (ESM) with better computational complexities and compare these algorithms with the inverse composition (IC) and the hyperplane approximation (HA). Issues regarding the use of the IC and HA for 3-D tracking are discussed. We show that even though an iteration of ESM is computationally more expensive than an iteration of IC, the faster convergence rate makes it globally faster. The tracking algorithm was validated by using an omnidirectional sensor mounted on a mobile robot.