期刊文献+

以目标为中心的MCRBR视点空间投影方法

OBJECT-CENTRED VIEW SPACE PROJECTION METHOD WITH MULTI-CAMERA REVOLVED BATCH RENDERING
下载PDF
导出
摘要 三维目标的姿态随视点变化而不同,选择适当角度范围的多尺度投影图像为代表,建立三维目标的完备特征库,能够提高基于图像的三维目标识别率。以目标为观察中心,基于3ds MAX提出一种多摄像机旋转批量渲染的三维目标视点空间投影方法。首先建立目标的三维模型,设置目标模型位置和顶视图摄像机位置,然后利用max层级命令面板锁定其中一个轴向的角度,以等采样间隔复制摄像机,设置半球面运动路径,并约束到相应摄像机,最后设置投影图像的输出参数并建立批处理脚本,实现三维目标视点空间任意投影图像的自动保存。 The attitudes of three dimensional objects vary with the changes of view. Choosing the images to be multi-scale projected in appropriate angles range as the representation to establisb a complete features base for tbree dimensional objects, which can improve the recognition rate of image-based 3D objects. Taking object as the observation centre, and based on 3ds MAX platform, we offer a view space projection method for three dimensional objects with multi-camera revolved batch rendering. First, we construct three dimensional models for the ob- jects, set up the positions for model and top view camera. Then using max level to order the panel sticking to one of the axis angle, and copy the cameras with equal interval. We also set up the moving path of hemisphere, and constraint it to corresponding camera. In the end, we set up output parameters of the projected images as well as establish batch-processing script, and achieve the automatic preservation of random projection images of three dimensional objects view space.
出处 《计算机应用与软件》 CSCD 北大核心 2012年第12期84-86,107,共4页 Computer Applications and Software
基金 国家高技术研究发展计划课题创新基金项目(2010AAJ113 2011AAJ211)
关键词 三维目标识别 视点空间 投影3ds MAX Three dimensional object recognition View space Projection 3ds MAX
  • 相关文献

参考文献7

二级参考文献56

  • 1刘进,张天序.不变矩构造方法的研究[J].华中科技大学学报(自然科学版),2003,31(3):1-3. 被引量:11
  • 2D H巴拉德 王东泉译.计算机视觉[M].北京:科学出版社,1987..
  • 3钟玉琢.机械人视觉技术[M].北京:国防工业出版社,1994..
  • 4Horn B. Extended Gaussian images [C]//Proc of the IEEE, 1984, 72(12): 1671-1686.
  • 5Saupe D, Vranic D V. 3D model retrieval with spherical harmonies and moments [C]//Proceedings of the DAGM, 2001, Munich, Germany, 2001: 392- 397.
  • 6Chen D Y, Ouhyoung M, Tian X P, et al. On visual similarity based 3D model retrieval [C]//Computer Graphics Forum, 2003, 22(3): 223-232.
  • 7Ansary T F, Daoudi M, Vandeborre J P. A bayesian 3D search engine using adaptive views clustering[J]. IEEE Transactions on Multimedia, 2007, 9(1) : 78 - 88.
  • 8Shilane P, Min P, Kazhdan N, et al. The princeton shape benchmark [C]//Proceeding of the IEEE Shape Modeling International 2004(SMI'04). Washington, DC: IEEE Computer Society, 2004 : 167 - 178.
  • 9Petrou M, Kadyrov A. Affine invariant features from the trace transform [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(1) : 30 - 44.
  • 10Rahtu E, Heikkila J. Object classification with multi-scale autoconvolution [C]// Proceedings of the 17th International Conference on Pattern Recognition (ICPR'04). Washington, DIE, IEEE Computer Society, 2004, 3: 37-40.

共引文献20

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部