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首页> 外文期刊>The Visual Computer >NLME: a nonlinear motion estimation-based compression method for animated mesh sequence
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NLME: a nonlinear motion estimation-based compression method for animated mesh sequence

机译：NLME：一种基于非线性运动估计的动画网格序列压缩方法

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摘要

This paper proposes an efficient compression algorithm for animated three-dimensional meshes by introducing nonlinear transformations to model the motion field of deforming patches. First, a segmentation process is applied to separate the 3D model into different patches which have similar motion patterns through the sequence. Next, the motion of the resulting patches is accurately described by a nonlinear motion estimation model. The main idea is to exploit the temporal coherence of the geometry component by using a nonlinear predictor in order to get better approximation of vertex locations. Nonlinear motion transforms are computed at previous frame to match the subsequent ones. Moreover, an adaptive bit allocation algorithm is employed to determine the near-optimal number of bits for quantizing the prediction errors. The number of quantization bits for each segmented patch is determined by analyzing the geometry complexity of the patch and the statistical properties of the prediction errors. Finally, an extensive experimental study has been conducted to evaluate the coding efficiency of the proposed compression scheme. Simulation results demonstrate that the proposed method is very efficient in terms of rate-distortion performance, particularly for the animated models with non-rigid deformations, and outperforms the state-of-the-art methods.
机译：通过引入非线性变换对变形斑块的运动场进行建模，提出了一种有效的三维动画网格压缩算法。首先，应用分割过程将3D模型分离为不同的补丁，这些补丁在整个序列中具有相似的运动模式。接下来，通过非线性运动估计模型准确描述所得贴片的运动。主要思想是通过使用非线性预测器来利用几何成分的时间相干性，以获得更好的顶点位置近似值。非线性运动变换在前一帧进行计算以匹配后续运动。此外，采用自适应比特分配算法来确定用于量化预测误差的接近最优的比特数。通过分析补丁的几何复杂度和预测误差的统计属性，可以确定每个分段补丁的量化位数。最后，进行了广泛的实验研究，以评估提出的压缩方案的编码效率。仿真结果表明，所提出的方法在速率失真性能方面非常有效，特别是对于具有非刚性变形的动画模型，其性能优于最新方法。

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