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采用平面-空间颜色局部一致性的点云模型描述

A Point Cloud Representation Using Plane-Space-Local-Area-Color-Consistency

  • 摘要: 为了避免在建模过程中对动态模型进行网格化处理和纹理映射,获得较高的建模速度及良好的模型外观,提出一种基于点云模型的动态物体模型重建方法.通过分水岭分割原理进行图像分割并提取分水岭轮廓;然后采用剪影轮廓序列建模方法重建物体的稀疏点云模型;最后根据平面-空间颜色局部一致性原理扩充模型,获得稠密点云模型.实验结果表明,该方法能够快速生成紧致性描述且具有外观表象的三维模型.

     

    Abstract: In order to avoid meshing the dynamic three-dimensional model and mapping texture during the reconstruction of the dynamic object,and then acquire higher reconstruction speed as well as better surface appearance,we present a reconstruction method for dynamic object based on the fact of the plane-space-local-area-color-consistency.First,image segmentation for the every video frame is implemented and then the watershed contours are extracted.Next,the sparse point cloud is computed using the shape-from-silhouettes.Finally,the compact and colored point cloud is attained efficiently based on the plane-space-local-area-color-consistency.Experimental results demonstrate that the new approach can attain the promise.

     

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