A new method of 3D object recognition was proposed.
提出了一种三维物体的识别方法。
It can be used in the 2d object recognition, and extended to 3d object recognition.
这种方法可应用于2d目标识别，并可推广应用子3 D目标识别。
The matching computation for 3D shape of superquadric models is one key problem in 3D object recognition with superquadrics.
超二次模型形状匹配计算是应用超二次模型进行三维物体识别的一个关键问题。
This thesis mainly aiming at the method of algebraic character that is represented by SVD has done plenty of research work in the aspects of 3d object recognition and pose estimation.
本文主要针对以奇异值特征为代表的代数特征方法，在3d目标识别及姿态估计等方面做了大量研究工作。
Last, we apply the dual quaternion algorithm to matching algorithm of 3d object recognition and make use of least-squares technique to propose a matching method based on iterative closest point.
论文将对偶四元数法应用到三维物体识别的匹配算法中，利用最小二乘的思想提出了一种基于迭代最近点的匹配算法。
Technest\'s 3D sensing algorithm fuses data from multiple sensors to achieve high-resolution rapid 3D mapping and reliable object recognition.
该公司的3D算法能够从多个传感器融合数据，实现高清快速3D制图和可靠的目标识别。
In analysis and pattern recognition of petrographical images, 3d object reconstruction is an important research.
在石油地质图象分析和模式识别中，三维物体重建是很重要的研究。
Feature point matching is a key problem of computer vision and is frequently used in object recognition, image retrieval and 3d reconstruction and so on.
图像序列中的特征点匹配是计算机视觉中的一个基本问题，也是目标识别、图像检索以及3维重建等问题的基础。
Technest's 3d sensing algorithm fuses data from multiple sensors to achieve high-resolution rapid 3d mapping and reliable object recognition.
该公司的3d算法能够从多个传感器融合数据，实现高清快速3d制图和可靠的目标识别。
Technest's 3d sensing algorithm fuses data from multiple sensors to achieve high-resolution rapid 3d mapping and reliable object recognition.
该公司的3d算法能够从多个传感器融合数据，实现高清快速3d制图和可靠的目标识别。
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