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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Klein, K. Sequeira, V. |
| Copyright Year | 2000 |
| Description | Author affiliation: Fraunhofer Inst. for Comput. Graphics, Darmstadt, Germany (Klein, K.) |
| Abstract | In recent years, several methods of reconstructing 3D scenes from range images have been proposed. Currently, the factor limiting a fully automated reconstruction process is the lack of a sufficiently scalable planning algorithm for the acquisition step. We present a technique of iteratively planning the next view for a range scanner in an initially unknown, large indoor environment. When designing an algorithm suitable for architectural environments, two main problems have to be addressed. First, an objective function has to be defined to optimise the parameters of the next view. We propose an objective function based on the analysis of occlusions which takes into account both a quality criterion and the cost of the next acquisition. Second, the parameters of the next view have to be computed efficiently for a large search space with eight degrees of freedom. Our technique exploits hardware-accelerated rendering (OpenGL) in order to perform the expensive visibility computation, which reduces the computation time of one planning step to a few minutes. Results are shown for two large indoor scenes-an artificial scene and a real world room-with numerous self occlusions. |
| Starting Page | 943 |
| Ending Page | 948 |
| File Size | 696190 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780363485 |
| DOI | 10.1109/IROS.2000.893140 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-10-31 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Layout Robotics and automation Computer graphics Image reconstruction Process planning Iterative algorithms Indoor environments Design optimization Cost function Image analysis |
| Content Type | Text |
| Resource Type | Article |
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