A method of detecting 3D object orientation by multiview models

G. Qu, S. L. Wood
{"title":"A method of detecting 3D object orientation by multiview models","authors":"G. Qu, S. L. Wood","doi":"10.1109/MDSP.1989.97003","DOIUrl":null,"url":null,"abstract":"The problem of determining the approximate orientation of an object from multiview models is considered for the case in which the number of models if fixed but the viewing angles are arbitrary. The multiview models include the height and width of each projected image of a 3D object, topological information based on the edge image, some region information and the angles of each projected image. Assuming there is only one object being considered, an image is input in an arbitrary viewing direction (camera focal length and the distance between the camera and the object are known) and processed to obtain the edge image. The edge image coordinate data are transformed into normalized data with respect to focal length and distance. The height and width of the object are compared with the models' height and width to determine a set of candidates, and topological and region information are used for further matching to detect the approximate orientation. In their experiment the authors built the multiview models from 16 viewing angles, each roughly equal to 22.5 degrees .<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixth Multidimensional Signal Processing Workshop,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDSP.1989.97003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The problem of determining the approximate orientation of an object from multiview models is considered for the case in which the number of models if fixed but the viewing angles are arbitrary. The multiview models include the height and width of each projected image of a 3D object, topological information based on the edge image, some region information and the angles of each projected image. Assuming there is only one object being considered, an image is input in an arbitrary viewing direction (camera focal length and the distance between the camera and the object are known) and processed to obtain the edge image. The edge image coordinate data are transformed into normalized data with respect to focal length and distance. The height and width of the object are compared with the models' height and width to determine a set of candidates, and topological and region information are used for further matching to detect the approximate orientation. In their experiment the authors built the multiview models from 16 viewing angles, each roughly equal to 22.5 degrees .<>
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种多视图模型检测三维物体方向的方法
针对模型数量固定而视角任意的情况,研究了从多视图模型中确定物体近似方向的问题。多视图模型包括三维物体的每个投影图像的高度和宽度、基于边缘图像的拓扑信息、一些区域信息和每个投影图像的角度。假设只考虑一个物体,在任意观看方向输入图像(已知相机焦距和相机与物体之间的距离)并进行处理以获得边缘图像。将边缘图像坐标数据转换为关于焦距和距离的归一化数据。将目标的高度和宽度与模型的高度和宽度进行比较,确定一组候选对象,并利用拓扑和区域信息进行进一步匹配,以检测近似方向。在他们的实验中,作者从16个视角建立了多视角模型,每个视角大约等于22.5度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A filtering approach to the two-dimensional volume conductor forward and inverse problems A cross-correlation approach to astronomical speckle imaging A new robust method for 2-D sinusoidal frequency estimation Fast progressive reconstruction of a transformed image by the Hartley method Adaptive filter for processing of multichannel nonstationary seismic data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1