A new approach for photorealistic rendering of a class of objects at arbitrary illumination is presented. The approach of the authors relies entirely on image based rendering techniques. A scheme is utilized for re-il...A new approach for photorealistic rendering of a class of objects at arbitrary illumination is presented. The approach of the authors relies entirely on image based rendering techniques. A scheme is utilized for re-illumination of objects based on linear combination of low dimensional image representations. The minimum rendering condition of technique of the authors is three sample images under varying illumination of a reference object and a single input image of an interested object. Important properties of this approach are its simplicity, robustness and speediness. Experimental results validate the proposed rendering approach.展开更多
A neural statistical approach to the reconstruction of novel viewpoint image us ing general regression neural networks(GRNN) is presented. Different color value will be obtained by watching the same surface point of a...A neural statistical approach to the reconstruction of novel viewpoint image us ing general regression neural networks(GRNN) is presented. Different color value will be obtained by watching the same surface point of an object from different viewpoints due to specular reflection, and the difference is related to the pos ition of viewpoint. The relationship between the position of viewpoint and the c olor of image is non linear, neural network is introduced to make curve fitting , where the inputs of neural network are only a few calibrated images with obvio us specular reflection. By training the neural network, network model is obtaine d. By inputing an arbitrary virtual viewpoint to the model, the image of the vir tual viewpoint can be computed. By using the method presented here, novel viewpo int image with photo realistic property can be obtained, especially images with obvious specular reflection can accurately be generated. The method is an image based rendering method, geometric model of the scene and position of lighting are not needed.展开更多
Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions...Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions and wrong depth values.Most of the existing hole-filling methods work well in areas of low spatial activity but fail to obtain satisfactory results in high spatial activity regions.In this paper,we combine the depth based hole-filling and the adaptive recursive interpolation algorithm which is capable of handling edges passing through the missing areas.Accoring to the experimental results,we confirm that the depth based adaptive recursive interpolation algorithm can provide better rendering quality objectively and subjectively.展开更多
文摘A new approach for photorealistic rendering of a class of objects at arbitrary illumination is presented. The approach of the authors relies entirely on image based rendering techniques. A scheme is utilized for re-illumination of objects based on linear combination of low dimensional image representations. The minimum rendering condition of technique of the authors is three sample images under varying illumination of a reference object and a single input image of an interested object. Important properties of this approach are its simplicity, robustness and speediness. Experimental results validate the proposed rendering approach.
文摘A neural statistical approach to the reconstruction of novel viewpoint image us ing general regression neural networks(GRNN) is presented. Different color value will be obtained by watching the same surface point of an object from different viewpoints due to specular reflection, and the difference is related to the pos ition of viewpoint. The relationship between the position of viewpoint and the c olor of image is non linear, neural network is introduced to make curve fitting , where the inputs of neural network are only a few calibrated images with obvio us specular reflection. By training the neural network, network model is obtaine d. By inputing an arbitrary virtual viewpoint to the model, the image of the vir tual viewpoint can be computed. By using the method presented here, novel viewpo int image with photo realistic property can be obtained, especially images with obvious specular reflection can accurately be generated. The method is an image based rendering method, geometric model of the scene and position of lighting are not needed.
基金The MSIP(Ministry of Science,ICT & Future Planning),Korea,under the ITRC(Information Technology Research Center)support program(NIPA-2013-H0301-13-2006)supervised by the NIPA(National IT Industry Promotion Agency)
文摘Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions and wrong depth values.Most of the existing hole-filling methods work well in areas of low spatial activity but fail to obtain satisfactory results in high spatial activity regions.In this paper,we combine the depth based hole-filling and the adaptive recursive interpolation algorithm which is capable of handling edges passing through the missing areas.Accoring to the experimental results,we confirm that the depth based adaptive recursive interpolation algorithm can provide better rendering quality objectively and subjectively.
