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3-D Data Acquisition and Shape Recognition by Multiple Views

多视图 3D 数据采集和形状识别

基本信息

批准号：
60550266
负责人：
YACHIDA Masahiko
金额：
$ 1.02万
依托单位：
Faculty of Engineering Science, Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1985
资助国家：
日本
起止时间：
1985 至 1986
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-60550266/
关键词：
computer vision 3-D measurement object recognition shape recognition 形状認識

项目摘要

For recognition of 3-D shape and measurement of 3-D position it is important that a vision system can measure the 3-D data of dense points in the scene. One promising approach is to measure the distance on the basis of the triangulation principle from the disparity of two images. However, a problem of this binocular method is that it is not easy to find correspondence of feature points.In this research, we propose a new approach for this correspondence problem in which the correspondence problem can be solved geometrically by adding one more camera, that is, by trinocular vision. We have made the trinocular vision system and have made experiments on a variety of objects. From these experiments we have found that the geometrical constraints of the trinocular vision is very powerful for finding correspondence.However, when the density of edge points increases, chances of points which have multiple candidata points also increase. To solve this problem we also introduced other properties such as similarity of local properties and edge continuity. That is , when there are multiple candidates by geometrical constraints, we check similarity of local properties and edge continuity, and determine the true corresponding point.Using the above method, we have made experiments and have found that correct correspondence can be established even for complicated scene.

对于三维形状的识别和三维位置的测量，视觉系统能够测量场景中密集点的三维数据是非常重要的。一种有前途的方法是根据三角测量原理从两幅图像的视差测量距离。然而，这种双目方法的一个问题是，它是不容易找到对应的特征点，在这项研究中，我们提出了一种新的方法，其中对应问题可以解决几何增加一个摄像机，即通过三目视觉。我们已经制作了三目视觉系统，并对各种物体进行了实验。从这些实验中我们发现，三目视觉的几何约束对于寻找对应是非常强大的，然而，当边缘点的密度增加时，具有多个候选点的点的机会也增加。为了解决这个问题，我们还引入了其他属性，如局部属性的相似性和边缘连续性。即当存在多个受几何约束的候选点时，通过检查局部属性的相似性和边缘的连续性，确定真正的对应点，并利用上述方法进行了实验，发现即使在复杂的场景中也能建立正确的对应。