摘要
Most of local feature descriptors assume that the scene is planar. In the real scene, the captured images come from the 3-D world. 3-D corner as a novel invariant feature is important for the image matching and the object detection, while automatically discriminating 3-D corners from ordinary corners is difficult. A novel method for 3-D corner detection is proposed based on the image graph grammar, and it can detect the 3-D features of corners to some extent. Experimental results show that the method is valid and the 3-D corner is useful for image matching.
许多局部特征描述都假设场景是平面的,而在真实场景中捕捉到的图片都是来自三维世界。在图像匹配和目标检测中,三维角点作为一种包含三维信息的形状特征,是一种新的重要不变特征,但从普通角点中自动鉴选出三维角点比较困难。基于图像的图形文法提出一种新的三维角点检测方法。该方法在一定程度上能够检测出角点的三维特性。实验结果表明三维角点特征在图像匹配中是适用的,证明了所提出的方法的有效性。
