3D object articulation and motion estimation for efficient multiview image sequence coding

D. Tzovaras, Y. Kompatsiaris, M. Strintzis
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引用次数: 7

Abstract

This paper describes a procedure for model-based coding of all the channels of a multiview image sequence. The scheme is initialized by the adaptation of a wireframe model to the consistent depth information. Robust classification techniques are then used to obtain an articulated description of the foreground of the scene (head, neck, shoulders). The object articulation procedure is based on a novel scheme for the segmentation of the rigid 3D motion fields of the triangle patches of the 3D model object. Spatial neighborhood constraints are used to improve the reliability of the original triangle motion estimation. The motion estimation and motion field segmentation procedures are repeated iteratively until a satisfactory object articulation emerges. Rigid 3D motion estimation is performed next for each resulting sub-object. The performance of the resulting articulation method is evaluated experimentally.
高效多视点图像序列编码的三维目标衔接和运动估计
本文描述了一种基于模型的多视点图像序列所有通道的编码方法。该方案通过将线框模型适配一致的深度信息来初始化。然后使用鲁棒分类技术来获得场景前景(头部,颈部,肩部)的清晰描述。该方法基于一种新的三维模型物体三角形块的刚性三维运动场分割方案。利用空间邻域约束提高原三角形运动估计的可靠性。运动估计和运动场分割过程迭代重复,直到出现满意的目标清晰度。接下来对每个结果子对象执行刚性3D运动估计。实验评估了所得到的发音方法的性能。
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