GPU-Based Occlusion Minimisation for Optimal Placement of Multiple 3D Cameras
| Autor: | Joacim Dybedal, Geir Hovland |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry 010401 analytical chemistry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology 01 natural sciences Minimisation (clinical trials) 0104 chemical sciences CUDA Viewing frustum Occlusion 0202 electrical engineering electronic engineering information engineering Computer vision Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA). |
| DOI: | 10.1109/iciea48937.2020.9248399 |
| Popis: | This paper presents a fast GPU-based solution to the 3D occlusion detection problem and the 3D camera placement optimisation problem. Occlusion detection is incorporated into the optimisation problem to return near-optimal positions for 3D cameras in environments containing occluding objects, which maximises the volume that is visible to the cameras. In addition, the authors’ previous work on 3D sensor placement optimisation is extended to include a model for a pyramid-shaped viewing frustum and to take the camera’s pose into account when computing the optimal position. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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