Patent
3d scanning and positioning interface
TL;DR: A scanner, a scanner for scanning the surface geometry of the object and using the cumulative each frame based on the shape of the 3D point positioning, and an instruction generator, the indication generator for generating the unreliable indicating detection of the pose estimation.
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Abstract: The present invention describes a system and method for providing an indication of the positioning of unreliability. The system comprising: a scanner, a scanner for scanning the surface geometry of the object and using the cumulative each frame based on the shape of the 3D point positioning; pose estimator for estimating the pose using the 3D the point estimate of the pose estimation scanner; unreliable pose detector, the detector position and orientation not reliable for determining whether the estimated position and attitude positioning constraints have insufficient; and an instruction generator, the indication generator for generating the unreliable indicating detection of the pose estimation. In one embodiment, the degree of freedom identifier identifies the estimated degrees of freedom have questions Pose. In one embodiment, the feature point detector detects the re-observed feature points and the pose estimation using feature points and the points to estimate the 3D pose of the estimated, and the unreliable detector uses the position and orientation of the estimated feature points identified as unreliable pose pose estimation.
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References
KinectFusion: Real-time dense surface mapping and tracking
Richard Newcombe,Shahram Izadi,Otmar Hilliges,David Molyneaux,David Kim,Andrew J. Davison,Pushmeet Kohi,Jamie Shotton,Steve Hodges,Andrew Fitzgibbon +9 more
- 26 Oct 2011
TL;DR: A system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware, which fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real- time.
Reliable 3D surface acquisition, registration and validation using statistical error models
J. Guehring
- 28 May 2001
TL;DR: A complete data acquisition and processing chain for the reliable inspection of industrial parts considering anisotropic noise is presented, which considers statistical information to decide whether the differences are significant.
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