【摘要】 本文提出了一种基于信息融合的物体三维特征提取方法,该方法利用两幅互相配准的三维测距图像和灰度图像,来提取多面体的三维特征.首先,通过分析灰度图像中的灰度变化及测距图像中的测距值变化,求取各自图像中物体的特征点及特征边;然后,利用两配准图像之间的对应关系,求得所有特征点、面与多边形在测距图像中的三维表示;接着,通过分析三维测距图像中所测得的各候选平面上特定点与边处的曲率及法向,验证候选平面;最后,利用验证后的各个平面,构成一个三维物体的层次表示.实验表明,该方法是有效可行的.更多还原

【Abstract】 This presentation proposes a method, based on data fusion, to obtain 3D features of polyhedrons using co-registered range and intensity images. First, feature points and edges of the candidate planes of the objects in the intensity and range images are acquired by analysing the intensity and range variation. Then, all the 3D candidate vertices, edges and planes in the range image can be got using the correspondence of the two co-registered images. Next, the candidate planes are verified by computing and analysing the curvatures and normals at some feature points and edges on the candidate planes in the range image. Finally, the verified candidates are regarded as actual planes if the sensed object, and are used to construct a hierarchical representation of the object. Experiment results have been given to show the feasibility of the proposed approach.更多还原