Visual reconstruction
A new development in camera calibration: calibrating a pair of mobile cameras
International Journal of Robotics Research
Accumulator-based inexact matching using relational summaries
Machine Vision and Applications
A camera calibration technique using three sets of parallel lines
Machine Vision and Applications
BONSAI: 3D Object Recognition Using Constrained Search
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
3d object recognition using invariant feature indexing of interpretation tables
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Efficient Data Structures for Model-Based 3-D Object Recognition and Localization from Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
Computer vision and applications: a guide for students and practitioners
Computer vision and applications: a guide for students and practitioners
Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
Computer Vision
Hierarchical Data Structures and Algorithms for Computer Graphics
IEEE Computer Graphics and Applications
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
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Techniques are proposed to support the video based development of systems for indoor exploration with mobile robots. The technique of redundant programming is often used to improve the reliability of operating systems, but the use of this technique is not common for CV (computer vision) applications. Also a new technique to create CAD (computer aided design) models from image data is described. These techniques were used for the development of an RV (robot vision) program. The observed recognition power exceeds the abilities of sophisticated but conventional programs clearly. This is documented with sample images, which show a table that has been taken from different distances. The quality of the images is very bad due to the fact that a camera was taken which has a very low resolution. Additionally the detection of the table was hampered, because the illumination in the images varied considerably. Sometimes the table was placed very near by a window with strong exposure to sunlight. Over-exposure of the table complicated the reconstruction because of this problem. Sometimes other objects irritated the detection. The program handled all these difficulties impressionably although it used no calibration techniques. No other robot-vision program is documented in the literature that gained the reported recognition rate.