系统仿真学报 ›› 2015, Vol. 27 ›› Issue (10): 2508-2513.

• 虚拟现实与可视化 • 上一篇    下一篇

基于深度图的可视外壳凹面优化

陈国军, 韦鑫   

  1. 中国石油大学(华东) 计算机与通信工程学院,青岛 266580
  • 收稿日期:2015-05-14 修回日期:2015-07-31 出版日期:2015-10-08 发布日期:2020-08-07
  • 作者简介:陈国军(1968-),男,江苏如东,博士,副教授,研究方向为图形图像处理,虚拟现实;韦鑫(1988-),女,山东东营,硕士,研究方向为图形图像处理。
  • 基金资助:
    虚拟现实技术与系统国家重点实验室开放基金(BUAA-VR-15KF-13)

Optimize Visual Hull with Concave Based on Depth Map

Chen Guojun, Wei Xin   

  1. College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, China
  • Received:2015-05-14 Revised:2015-07-31 Online:2015-10-08 Published:2020-08-07

摘要: 传统基于RGB图像的可视外壳能恢复物体的外围轮廓却无法还原物体的凹面部分,而基于深度图像的可视外壳虽然可以还原凹面域,但其结果的边缘粗糙,轮廓不明晰。深度图像与RGB图像的可视外壳融合的计算方法,是为解决单一方式的可视外壳不足而提出的,它基于体素剖分的思想,根据深度图和RGB图像分别构建可视外壳,根据两种可视外壳的计算结果进行凹面分析和可视外壳融合,利用CUDA基于GPU实现并行加速。实验表明:融合算法能够还原出具有复杂凹面域物体的可视外壳,并且有良好的精度及实时性。

关键词: 深度图, 可视外壳, 凹面还原, 三维重建

Abstract: Traditional method based on color image can recover the boundary of an object, but it can't recover the concave part. Although reconstruction based on depth image can revert the concave part, but the result has bad boundary which means that the edge information lost seriously. The method that fused the depth and RGB image was proposed to solve the individual shortcomings. Based on space subdivision the origin visual hull was computed based RGB image and depth image individually. In the following step, the two type visual hulls were combined for analyzing concave area and then fused into one. A parallel scheme under the CUDA platform based on GPU was implemented to accelerate processing speed. The results indicate that the proposed method can recover the visual hull for an object with complicated concave area and performs well in the part of speed and quality.

Key words: depth image, visual hull, concave revert, 3D reconstruction

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