基于差分图像信息和运动边缘几何关系的机器人视觉系统

N. Harle, Min Xi
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引用次数: 1

摘要

对于机器人视觉来说,重要的是从一系列图像帧中提取特征,而不是从单个图像中提取特征。视频序列中图像帧的高速率提供了大量的信息。提取这些信息使得有必要引入几个处理阶段,这些处理阶段以不同的速度异步交换数据。早期处理阶段的算法必须快速,以便处理每一帧,而后期提取高r级信息的算法可能会更慢,更复杂。在本文中,我们假设摄像机可以被控制地移动。提出了一种机器人视觉系统的结构,该系统检测图像序列中边缘的运动,并通过解释运动来分配三维空间。它考虑由于静态环境和相机的移动而产生的边缘以及由于移动物体而产生的边缘。最后一个阶段是对象识别。整个系统由“视觉管理器”监督,它控制摄像机和感兴趣的区域,从而确保在有限的处理能力范围内执行重要任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robot Vision System Using Differential Image Information And Geometrical Relations Of Moving Edges
For robot vision, it is important to extract features from a sequence of image frames rather than from each image individually. The high rate of image frames in a video sequence supplies a high amount of information. Extracting this information makes it necessary to introduce several processing stages which exchange data asynchronously and rhus working at different speed. Algorithms in the early processing stage have to be fast in order to work on each frame whereas algorithms in later stages which extract information on a hight:r level may be slower and more complex. For this paper, it is assumed that the camera can be moved in a controlled way. A structure of a robot vision system is presented which detects the movements of edges in a sequence of images and assigns the third dimension by interpreting the movements. It considers edges due to the static environment and the movement of the camera and edges due to moving: objects. A last stage deals with the object recognition. The whole system is supervised by a "Vision Manager" which controls the camera as well as the regions of interest and thus ensures that important tasks are carried out within a limited range of processing power.
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