High Quality Free Viewpoint Synthesis Using Multi-view Images with Depth Information

I. Tsuchida, Fan Chen, J. Izawa, K. Kotani
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Abstract

Compared to conventional synthesis methods of free viewpoint images that use only multi-view images, our research synthesizes high quality free viewpoint images by using multi-view depth information as well as the images. By recovering high resolution and high precision 3D shapes from multi-view information, high quality free viewpoint images are synthesizable. Our research captures the scene by acquiring its multi-view depth appearance information, using a laser range finder. By performing camera parameter estimation, multi-view 3D shape integration and depth estimation, high quality free viewpoint images for any scene are synthesized. The performance of our method has been investigated by experimental results.
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使用具有深度信息的多视图图像的高质量免费视点合成
与传统的仅使用多视点图像的自由视点图像合成方法相比,我们的研究利用多视点深度信息和图像合成高质量的自由视点图像。通过从多视点信息中恢复高分辨率、高精度的三维形状,合成高质量的自由视点图像。我们的研究通过使用激光测距仪获取场景的多视角深度外观信息来捕获场景。通过相机参数估计、多视角三维形状集成和深度估计,合成出任意场景的高质量自由视点图像。实验结果验证了该方法的性能。
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