Joint spatial and frequency domain motion analysis

N. Ahuja, A. Briassouli
{"title":"Joint spatial and frequency domain motion analysis","authors":"N. Ahuja, A. Briassouli","doi":"10.1109/FGR.2006.68","DOIUrl":null,"url":null,"abstract":"Traditionally, motion estimation and segmentation have been performed mostly in the spatial domain, i.e., using the luminance information in the video sequence. Frequency domain representation offers an alternative, rich source of motion information, which has been used to a very limited extent in the past, and on relatively simple problems such as image registration. We review our work during the last few years on an approach to video motion analysis that combines spatial and Fourier domain information. We review our methods for (1) basic (translation and rotation) motion estimation and segmentation, for multiple moving objects, with constant as well as time varying velocities; and (2) more complicated motions, such as periodic motion, and periodic motion superposed on translation. The joint space analysis leads to more compact and computationally efficient solutions than existing techniques","PeriodicalId":109260,"journal":{"name":"7th International Conference on Automatic Face and Gesture Recognition (FGR06)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Conference on Automatic Face and Gesture Recognition (FGR06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGR.2006.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Traditionally, motion estimation and segmentation have been performed mostly in the spatial domain, i.e., using the luminance information in the video sequence. Frequency domain representation offers an alternative, rich source of motion information, which has been used to a very limited extent in the past, and on relatively simple problems such as image registration. We review our work during the last few years on an approach to video motion analysis that combines spatial and Fourier domain information. We review our methods for (1) basic (translation and rotation) motion estimation and segmentation, for multiple moving objects, with constant as well as time varying velocities; and (2) more complicated motions, such as periodic motion, and periodic motion superposed on translation. The joint space analysis leads to more compact and computationally efficient solutions than existing techniques
关节空间和频域运动分析
传统上,运动估计和分割主要是在空间域中进行的,即利用视频序列中的亮度信息。频域表示提供了一种替代的、丰富的运动信息源,它在过去被用于非常有限的程度,以及相对简单的问题,如图像配准。我们回顾了我们的工作,在过去几年的视频运动分析的方法,结合空间和傅里叶域信息。我们回顾了我们的方法:(1)基本(平移和旋转)运动估计和分割,对于多个运动物体,具有恒定和时变的速度;(2)更复杂的运动,如周期运动,和周期运动叠加在平移上。与现有技术相比,关节空间分析可以得到更紧凑、计算效率更高的解决方案
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信