Kinect-based easy 3D object reconstruction
Inspired by the recently developed KinectFusion technique, which is able to reconstruct a 3D scene in real time through moving Kinect, we consider improving KinectFusion for 3D reconstruction of a real object. We make some adaptations to KinectFusion so as to identify the object-of-interest and sepa...
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| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99335 http://hdl.handle.net/10220/17250 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Inspired by the recently developed KinectFusion technique, which is able to reconstruct a 3D scene in real time through moving Kinect, we consider improving KinectFusion for 3D reconstruction of a real object. We make some adaptations to KinectFusion so as to identify the object-of-interest and separate the 3D object model from the entire 3D scene. Moreover, considering that the 3D object model generated by KinectFusion often contains some clearly visible outliers due to the noisy Kinect data, we propose a refinement scheme to remove the outliers. Our basic idea is to make use of the existing powerful 2D segmentation tool to refine the silhouette in each color image and then form visual hull via the refined dense silhouettes to improve the 3D object model. Experimental results show improved performance. |
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