基于相对几何特征的部分相似人体运动检索

Song-Le Chen, Zhengxing Sun, Yi Li, Qian Li
{"title":"基于相对几何特征的部分相似人体运动检索","authors":"Song-Le Chen, Zhengxing Sun, Yi Li, Qian Li","doi":"10.1109/ICDH.2012.91","DOIUrl":null,"url":null,"abstract":"With the emergence of different kinds and styles of movements in the motion database, the methods which only support overall similarity motion retrieval can't meet the needs of practical applications. In this paper, we present an effective method based on relative geometry features to support partial similarity human motion retrieval. The key components of our approach include effective feature selection by Adaboost, initial feature weight predication for a query through regression model and effective relevance feedback based on feature weight adjustment. Experimental results prove the effectiveness of our proposed method.","PeriodicalId":308799,"journal":{"name":"2012 Fourth International Conference on Digital Home","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Partial Similarity Human Motion Retrieval Based on Relative Geometry Features\",\"authors\":\"Song-Le Chen, Zhengxing Sun, Yi Li, Qian Li\",\"doi\":\"10.1109/ICDH.2012.91\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the emergence of different kinds and styles of movements in the motion database, the methods which only support overall similarity motion retrieval can't meet the needs of practical applications. In this paper, we present an effective method based on relative geometry features to support partial similarity human motion retrieval. The key components of our approach include effective feature selection by Adaboost, initial feature weight predication for a query through regression model and effective relevance feedback based on feature weight adjustment. Experimental results prove the effectiveness of our proposed method.\",\"PeriodicalId\":308799,\"journal\":{\"name\":\"2012 Fourth International Conference on Digital Home\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Digital Home\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDH.2012.91\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Conference on Digital Home","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDH.2012.91","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

随着运动数据库中不同类型和风格的运动的出现,仅支持整体相似运动检索的方法已不能满足实际应用的需要。本文提出了一种基于相对几何特征的人体运动部分相似检索方法。该方法的关键组成部分包括Adaboost的有效特征选择,通过回归模型对查询进行初始特征权重预测,以及基于特征权重调整的有效关联反馈。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Partial Similarity Human Motion Retrieval Based on Relative Geometry Features
With the emergence of different kinds and styles of movements in the motion database, the methods which only support overall similarity motion retrieval can't meet the needs of practical applications. In this paper, we present an effective method based on relative geometry features to support partial similarity human motion retrieval. The key components of our approach include effective feature selection by Adaboost, initial feature weight predication for a query through regression model and effective relevance feedback based on feature weight adjustment. Experimental results prove the effectiveness of our proposed method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:604180095
Book学术官方微信