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Synthetic Video Generation with Complex Camera Motion Patterns to Evaluate Sprite Generation

机译:具有复杂摄像机运动模式的合成视频生成,以评估子画面生成

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Without the ground truth image, there is no proper objective method to evaluate sprite generation. In this paper, we propose several complex camera motion patterns to generate synthetic video from original images. Our camera motion patterns include Rotation, Affine, and Pan-Tilt-Zoom (PTZ) transformations. In addition, they also include combined patterns. Subsequently, we applied sprite generation to the synthetic videos. Objective evaluation is performed by comparing the ground truth image and sprite based on Peak-Signal-to-Noise Ratio (PSNR) and size. Pattern algebra file is also provided for estimating the accuracy of sprite generation with respect to global motion parameters. Our result indicates that frame PSNR, picture PSNR, size, ground truth image, and pattern algebra file are good indicators of sprite quality.
机译:没有地面真相图像,就没有合适的客观方法来评估子画面的生成。在本文中,我们提出了几种复杂的摄像机运动模式,可以从原始图像生成合成视频。我们的相机运动模式包括“旋转”,“仿射”和“平移-倾斜-缩放”(PTZ)转换。此外,它们还包括组合模式。随后,我们将子画面生成应用于合成视频。通过根据峰-信噪比(PSNR)和大小比较地面真实图像和子画面来执行客观评估。还提供了模式代数文件,用于估计相对于全局运动参数的子画面生成的准确性。我们的结果表明帧PSNR,图片PSNR,大小,地面真实图像和模式代数文件是精灵质量的良好指标。

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