Image Information Extraction Model Based onMulti-features of K-nearest Neighbors
- 10.2991/icmmct-16.2016.355How to use a DOI?
- K-nearest neighbor; multi-feature; BRDF modeling; information extraction
Bidirectional Reflectance Distribution Function (BRDF) and Bidirectional Texture Function (BTF) are two major methods used to describe the reflectance of light at a surface under different illuminations and different views. However, due to a large number of measurement data, an efficient compression method is needed. Meanwhile, the requirements of real-time rendering should be met. Under this background, this paper mainly does some exploratory research on BRDF modeling methods based on the qualitative measurements of textures. By conducting BRDF modeling on the measurements derives with different acquisition devices, it obtains the illumination properties of textures. Finally, combined with the property information of textures on the surface of object, under a new light source, from a new viewpoint, it renders the relighting effect of the object under a new light source.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Anmin Xu PY - 2016/03 DA - 2016/03 TI - Image Information Extraction Model Based onMulti-features of K-nearest Neighbors BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology PB - Atlantis Press SP - 1782 EP - 1786 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-16.2016.355 DO - 10.2991/icmmct-16.2016.355 ID - Xu2016/03 ER -