DeepLight: light source estimation for augmented reality using deep learning

Author:

Kán Peter,Kafumann Hannes

Funder

TU Wien

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Reference34 articles.

1. Agusanto, K., Li, L., Chuangui, Z., Sing, N.W.: Photorealistic rendering for augmented reality using environment illumination. In: IEEE ISMAR, pp. 208–218 (2003)

2. Boom, B., Orts-Escolano, S., Ning, X., McDonagh, S., Sandilands, P., Fisher, R.B.: Point light source estimation based on scenes recorded by a RGB-D camera. In: British Machine Vision Conference (2013)

3. Boom, B.J., Orts-Escolano, S., Ning, X.X., McDonagh, S., Sandilands, P., Fisher, R.B.: Interactive light source position estimation for augmented reality with an RGB-D camera. Comput. Animat. Virtual Worlds 28(1), 5149–5159 (2015)

4. Dante, A., Brookes, M.: Precise real-time outlier removal from motion vector fields for 3D reconstruction. In: International Conference on Image Processing, vol. 1 (2003)

5. Debevec, P.: Rendering synthetic objects into real scenes: bridging traditional and image-based graphics with global illumination and high dynamic range photography. In: SIGGRAPH, pp. 189–198. ACM, New York (1998)

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