运动视频中基于草图的运动查询

Ihab Al Kabary, H. Schuldt
{"title":"运动视频中基于草图的运动查询","authors":"Ihab Al Kabary, H. Schuldt","doi":"10.1109/ISM.2013.60","DOIUrl":null,"url":null,"abstract":"The advent of pen-based user interfaces has facilitated several natural ways for human-computer interaction. One example is sketch-based retrieval, i.e., the search for (multimedia) objects on the basis of sketches as query input. So far, work has focused mainly on sketch-based image retrieval. However, more and more application domains also benefit from sketches as query input for searching in video collections. Enabling spatial search in videos, in the form of sketch-based motion queries, is increasingly demanded by coaches and analysts in team sports as a novel and innovative tool for game analysis. Even though game analysis is already a major activity in this domain, it is still mostly based on manual selection of video sequences. In this paper, we present Sport Sense, a first approach to enabling intuitive and efficient video retrieval using sketch-based motion queries. This is accomplished by using videos of games in team sports, together with an overlay of meta data that incorporates spatio-temporal information about various events. Sport Sense exploits spatio-temporal databases to store, index, and retrieve the tracked information at interactive response times. Moreover, it provides first intuitive user input interfaces for sketches representing motion paths. A particular challenge is to convert the users' sketches into spatial queries and to execute these queries in a flexible way that allows for some controlled deviation between the sketched path and the actual movement of the players and/or the ball. The evaluation results of Sport Sense show that this approach to sketch-based retrieval in sports videos is both very effective and efficient.","PeriodicalId":6311,"journal":{"name":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","volume":"25 1","pages":"309-314"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Towards Sketch-Based Motion Queries in Sports Videos\",\"authors\":\"Ihab Al Kabary, H. Schuldt\",\"doi\":\"10.1109/ISM.2013.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advent of pen-based user interfaces has facilitated several natural ways for human-computer interaction. One example is sketch-based retrieval, i.e., the search for (multimedia) objects on the basis of sketches as query input. So far, work has focused mainly on sketch-based image retrieval. However, more and more application domains also benefit from sketches as query input for searching in video collections. Enabling spatial search in videos, in the form of sketch-based motion queries, is increasingly demanded by coaches and analysts in team sports as a novel and innovative tool for game analysis. Even though game analysis is already a major activity in this domain, it is still mostly based on manual selection of video sequences. In this paper, we present Sport Sense, a first approach to enabling intuitive and efficient video retrieval using sketch-based motion queries. This is accomplished by using videos of games in team sports, together with an overlay of meta data that incorporates spatio-temporal information about various events. Sport Sense exploits spatio-temporal databases to store, index, and retrieve the tracked information at interactive response times. Moreover, it provides first intuitive user input interfaces for sketches representing motion paths. A particular challenge is to convert the users' sketches into spatial queries and to execute these queries in a flexible way that allows for some controlled deviation between the sketched path and the actual movement of the players and/or the ball. The evaluation results of Sport Sense show that this approach to sketch-based retrieval in sports videos is both very effective and efficient.\",\"PeriodicalId\":6311,\"journal\":{\"name\":\"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)\",\"volume\":\"25 1\",\"pages\":\"309-314\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISM.2013.60\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2013.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

基于笔的用户界面的出现促进了人机交互的几种自然方式。一个例子是基于草图的检索,即基于草图作为查询输入来搜索(多媒体)对象。到目前为止,工作主要集中在基于草图的图像检索上。然而,越来越多的应用领域也受益于草图作为视频集合搜索的查询输入。在视频中以基于草图的运动查询的形式进行空间搜索,作为一种新颖和创新的游戏分析工具,越来越多地被团队运动的教练和分析师要求。尽管游戏分析已经是该领域的主要活动,但它仍然主要基于手动选择视频序列。在本文中,我们提出了Sport Sense,这是使用基于草图的运动查询实现直观高效视频检索的第一种方法。这是通过使用团队运动中的游戏视频,以及包含各种事件时空信息的元数据叠加来实现的。Sport Sense利用时空数据库来存储、索引和检索交互式响应时间的跟踪信息。此外,它为表示运动路径的草图提供了第一个直观的用户输入界面。一个特别的挑战是将用户的草图转换为空间查询,并以一种灵活的方式执行这些查询,允许在草图路径和球员和/或球的实际运动之间有一些可控的偏差。体育感官的评价结果表明,该方法在体育视频中基于速写的检索是非常有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Towards Sketch-Based Motion Queries in Sports Videos
The advent of pen-based user interfaces has facilitated several natural ways for human-computer interaction. One example is sketch-based retrieval, i.e., the search for (multimedia) objects on the basis of sketches as query input. So far, work has focused mainly on sketch-based image retrieval. However, more and more application domains also benefit from sketches as query input for searching in video collections. Enabling spatial search in videos, in the form of sketch-based motion queries, is increasingly demanded by coaches and analysts in team sports as a novel and innovative tool for game analysis. Even though game analysis is already a major activity in this domain, it is still mostly based on manual selection of video sequences. In this paper, we present Sport Sense, a first approach to enabling intuitive and efficient video retrieval using sketch-based motion queries. This is accomplished by using videos of games in team sports, together with an overlay of meta data that incorporates spatio-temporal information about various events. Sport Sense exploits spatio-temporal databases to store, index, and retrieve the tracked information at interactive response times. Moreover, it provides first intuitive user input interfaces for sketches representing motion paths. A particular challenge is to convert the users' sketches into spatial queries and to execute these queries in a flexible way that allows for some controlled deviation between the sketched path and the actual movement of the players and/or the ball. The evaluation results of Sport Sense show that this approach to sketch-based retrieval in sports videos is both very effective and efficient.
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
期刊最新文献
The LectureSight System in Production Scenarios and Its Impact on Learning from Video Recorded Lectures Similarity-Based Browsing of Image Search Results Efficient Super Resolution Using Edge Directed Unsharp Masking Sharpening Method A Fluorescent Mid-air Screen Towards Sketch-Based Motion Queries in Sports Videos
×
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