双目主动视觉监测平台下的目标识别

摘要

Scale Invariant Features Transform(SIFT) algorithm is stable to rotating, scale changes and visual angle changes of the target, so this paper proposes an object identification method for a new visual monitoring platform—the baseline based on circle track adjustable binocular active vision platform. By establishing the off-line database of multifaceted SIFT features, it converts three-dimensional object into two-dimensional characterization, and uses it to realize object recognition three-dimensional space, so that the matching and recognition efficiency is improved.Experimental results show that the method can identify objects real time and accurately.%利用对目标旋转、尺度变化、视角变化等具有稳定性的尺度不变特征变换(SIFT)算法,提出一种适用于基于圆轨的基线可调双目主动视觉监测平台的目标识别方法,通过离线建立物体的多侧面SIFT特征点数据库,将三维空间的目标转换为二维特征描述,利用二维特征描述实现三维空间目标的识别,以提高匹配识别效率.实验结果表明,该方法能实时准确地识别目标.