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https://doi.org/10.1109/ICIP.2011.6116696
Title: | Dense interpolation of 3D points based on surface and color | Authors: | Jia Z. Chang Y.-J. Lin T.-H. Chen T. |
Keywords: | 3D-interpolation MRF Surface fitting |
Issue Date: | 2011 | Citation: | Jia Z., Chang Y.-J., Lin T.-H., Chen T. (2011). Dense interpolation of 3D points based on surface and color. Proceedings - International Conference on Image Processing, ICIP : 869-872. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2011.6116696 | Abstract: | A laser scan is useful in building the 3D model, and in one run it can capture thousands of 3D points. However these 3D points are sparse compared to a normal image, which can easily have millions of pixels. To achieve a denser 3D map, 3D-interpolation is applied to each pixel in the image. In this work we propose an algorithm to combine the 3D geometry and the color for 3D-interpolation. We segment the 3D points based on their latent surfaces, and combine the surfaces with color through Markov Random Field. We find that the 3D geometry provides rich information for interpolation: 3D points with similar colors can be robustly clustered where not possible in the color space, and the interpolation can be performed on a better fitting surface rather than on the locally linear ones. Our experiments show that the proposed algorithm outperforms the baselines. | Source Title: | Proceedings - International Conference on Image Processing, ICIP | URI: | http://scholarbank.nus.edu.sg/handle/10635/146150 | ISBN: | 9781457713033 | ISSN: | 15224880 | DOI: | 10.1109/ICIP.2011.6116696 |
Appears in Collections: | Staff Publications |
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