面向服务机器人的3D场景理解方法研究

项目名称： 面向服务机器人的3D场景理解方法研究

项目编号： No.61273360

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 原魁

作者单位： 中国科学院自动化研究所

项目金额： 82万元

中文摘要： 准确、快速地进行3D场景理解对服务机器人具有重要意义。由于将3D物理世界映射为2D图像会造成大量的信息丢失，利用普通视觉系统进行3D场景理解时存在很大困难。虽然利用深度信息传感器可以直接得到物体和场景的2.5D信息，但由于目前可用于服务机器人的深度信息传感器存在分辨率较低、不能准确反映物体细节、精度受外部条件影响较大等缺点，因此，也难以很好地满足进行3D场景理解的需要。本课题针对服务机器人的特点，提出一种将Marr视觉理论框架和主动视觉理论框架相结合的新的3D场景理解算法框架。该算法框架利用双目视觉提取场景中的"注意区域"并进行场景的深度层次划分，利用主动视觉提取"注意区域"的深度信息和图像特征，并在此基础上进行3D物体提取和3D场景理解。该算法框架发挥了Marr视觉理论和主动视觉理论两者的优势，利用主动视觉有效减少进行3D场景理解的计算量，对提高服务机器人的智能水平和实用性具有重要意义。

中文关键词： 服务机器人；3D场景理解；主动视觉；视觉伺服；

英文摘要： It is of great significance for service robots to comprehend 3D scenes accurately and rapidly. Since a large amount of information is lost while mapping the 3D physical world to 2D images, it is rather difficult for conventional machine vision systems to understand 3D scenes. Although 2.5D information of objects and scenes can be obtained directly with depth sensors, there exist some drawbacks in the current depth sensors available in service robots, such as relatively low resolutions with limited capability to reflect the details of objects and fluctuant precisions susceptible to external conditions, making them unsatisfactory in building a system to comprehend 3D scenes. With the characteristics of service robot in consideration, this project proposes a new algorithm framework to interpret 3D scenes, which combines the computer vision framework of Marr and the active vision framework. On extracting the region of interest (ROI) and acquiring the general depth gradation of the scene through binocular vision, the detailed depth information and image features in the ROI are obtained with active vision. Recognition of 3D objects and comprehension of 3D scenes are then realized on this basis. This algorithm framework exploits both the advantages of Marr's computer vision theory and active vision theory, and greatly

英文关键词： Service Robot；Interpreting 3D scenes；Active Vision；Vision Servo；