Review and analysis of solutions of the three point perspective pose estimation problem
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans
Journal of Intelligent and Robotic Systems
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real Time Localization and 3D Reconstruction
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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Most existing approaches to indoor localization focus on using either cameras or laser scanners as the primary sensor for pose estimation. In scan matching based localization, finding scan point correspondences across scans is challenging as individual scan points lack unique attributes. In camera based localization, one has to deal with images with few or no visual features as well as scale factor ambiguities to recover absolute distances. In this paper, we develop multimodal approaches for two indoor localization problems by fusing a camera and laser scanners in order to alleviate the drawbacks of each individual modality. For our first problem we recover 3 Degrees of Freedom (DoF) of a camera-laser rig on a rolling cart in a 2D plane, by using visual odometry to facilitate scan correspondence estimation. We demonstrate this approach to result in a 0.3% loop closure error for a 60m loop around the interior corridor of a building. In our second problem, we recover 6 DoF of a human operator carrying a backpack system mounted with sensors in 3D, by merging rotation estimates from scan matching and translation estimates from visual odometry, resulting in a 1% loop closure error.