首页> 外文期刊>Journal of computer sciences >Data Extraction from Computer Acquired Images of a Given 3D Environment for Enhanced Computer Vision and its Applications in Kinematic Design of Robos | Science Publications
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Data Extraction from Computer Acquired Images of a Given 3D Environment for Enhanced Computer Vision and its Applications in Kinematic Design of Robos | Science Publications

机译:从给定的3D环境中获取计算机图像以增强计算机视觉的数据提取及其在Robos运动学设计中的应用|科学出版物

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> Problem statement: Literature review was mainly aiming at recognition of objects by the computer and to make explicit the information that is implicit in the attributes of 3D objects and their relative positioning in the 3D Environment (3DE) as seen in the 2D images. However quantitative estimate of position of objects in the 3DE in terms of their x, y and z co-ordinates was not touched upon. This issue assumes important dimension in areas like Kinematic Design of Robos (KDR), while the Robo is negotiating with z field or Depth Field (DF). Approach: The existing methods such as pattern matching used by Robos for Depth Visualization (DV) using a set of external commands, were reviewed in detail. A methodology was developed in this study to enable the Robo to quantify the depth by itself, instead of looking for external commands. Results: The Results are presented and discussed. The Results are presented and discussed. The major conclusions drawn based on the results were listed. Conclusion: The major contribution of the present study consists of computing the Depth (D1) corresponding to the depth (d) measured from the photographic image of a 3DE. It had been concluded that, there exists an excellent agreement between the computed depth D1 and the corresponding actual Depth (D). The percent deviation of D1 from D (DP) lies between
机译: > 问题陈述:文献综述的主要目的是通过计算机识别对象,并明确显示隐含在3D对象属性及其相对位置中的信息。如2D图像中所示的3D环境(3DE)。然而,关于3DE中的对象的x,y和z坐标的定量估计没有涉及。该问题在机器人运动设计(KDR)等领域具有重要意义,而机器人正在与z场或深度场(D F )进行谈判。 方法:详细讨论了Robos使用一组外部命令进行深度可视化(DV)的模式匹配之类的现有方法。在这项研究中开发了一种方法,以使机器人能够自行量化深度,而不用寻找外部命令。 结果:介绍并讨论结果。提出并讨论了结果。列出了基于结果得出的主要结论。 结论:本研究的主要贡献在于计算与从3DE的摄影图像测得的深度(d)相对应的深度(D 1 )。得出的结论是,在计算出的深度D 1 与相应的实际深度(D)之间存在极好的一致性。 D 1 与D(D P )的百分比偏差介于

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