计算机工程 ›› 2017, Vol. 43 ›› Issue (12): 242-247.doi: 10.3969/j.issn.1000-3428.2017.12.044

• 图形图像处理 • 上一篇    下一篇

基于立体视觉的鞋楦数字化研究

杨海清,郭更新   

  1. (浙江工业大学 信息工程学院,杭州 310023)
  • 收稿日期:2016-10-11 出版日期:2017-12-15 发布日期:2017-12-15
  • 作者简介:杨海清(1971—),男,副教授,主研方向为计算机视觉;郭更新,硕士研究生。
  • 基金项目:
    浙江省自然科学基金(LY13F010008);浙江省科技计划项目(2015F50009)。

Research on Shoelast Digitalization Based on Stereoscopic Vision

YANG Haiqing,GUO Gengxin   

  1. (College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)
  • Received:2016-10-11 Online:2017-12-15 Published:2017-12-15

摘要: 针对鞋楦图像在三维重建中的匹配问题,提出一种改进的鞋楦数字化方法。对鞋楦表面做纹理网格化处理,利用Harris与Laplace算子相结合的方法提取特征点,采用改进的去除误匹配方法进行精匹配,通过双目视觉三角测量法求出匹配点的三维坐标。使用迭代近邻点算法实现不同方向点集的坐标融合和三维拼接,对全部三维点云数据进行三角网格化和曲面拟合,完成鞋楦三维重建。实验结果表明,该方法能便捷、高效地实现鞋楦数字化重建,可满足个性化制鞋需求。

关键词: 鞋楦数字化, 特征提取, 立体匹配, 尺度不变特征变换, 坐标融合, 三维重建

Abstract: In order to solve image matching problem in 3D reconstruction of shoelast,this paper proposes an improved shoelast digitalization method.Shoelast surface texture is firstly gridded to form feature points,which are extracted by combining Harris and Laplace operators.The extracted feature points are precisely matched by an improved method of removing false match.The 3D coordinates of the matched feature points are obtained through binocular vision triangulation.Then,an Iterative Closest Point(ICP) algorithm is used on the point set with different directions for coordinate fusion and 3D mosaic.Finally,based on the whole point cloud data,the methods of triangulation and surface fitting are used for the 3D reconstruction of showlast.Experimental results show that this method can be conveniently and efficiently used for digital reconstruction of shoelast,which can be improved for personalized shoe-making demand.

Key words: shoelast digitalization, feature extraction, stereo matching, Scale Invariant Feature Transform(SIFT), coordinate fusion, 3D reconstruction

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