| Reconstruction of Novel Viewpoint lmage Using GRNN |
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| 作者姓名： | 李战委 孙济洲 张志强 |
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| 作者单位： | [1]HebeiUniversityofTechnology,Tianjin300130,China [2]SchoolofElectronicInformationEngineering,TianjinUniversity,Tianjin300072,China |
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| 摘 要： | A neural-statistical approach to the reconstruction of novel viewpoint image general regression neural networks(GRNN) is presented.Different color value will be obtained by watching the same surface point of an abject from different viewpoints due to specular reflection,and the difference is related to the position of viewpoint.The relationship between the position of vewpoint and the color 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 obvious specular reflection.By training the neural network,network model is obtained.By inputing an arbitrary virtual viewpoint to the model,the image of the virtual viewpoint can be computed.By using the method presented here,novel viewpoint 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.
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| 关 键 词： | 广义衰退神经网络 镜面反射 几何模型 图像描述法 |
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