A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Computer Vision and Image Understanding
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Special issue on registration and fusion of range images
Computer Vision and Image Understanding - Registration and fusion of range images
When and Why Are Visual Landmarks Used in Giving Directions?
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Alignment of Continuous Video onto 3D Point Clouds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose and Motion Recovery from Feature Correspondences and a Digital Terrain Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Urban 3D Reconstruction from Video
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The successful mission of an autonomous airborne system like an unmanned aerial vehicle (UAV) strongly depends on its accurate navigation. While GPS is not always available and pose estimation based solely on Inertial Measurement Unit (IMU) drifts, image-based navigation may become a cheap and robust additional pose measurement device. For the actual navigation update a landmark-based approach is used. It is essential that the used landmarks are well chosen. Therefore we introduce an approach for evaluating landmarks in terms of the matching distance, which is the maximum misplacement in the position of the landmark that can be corrected. We validate the evaluations with our 3D reconstruction system working on data captured from a helicopter.