Towards Sketch-Based Motion Queries in Sports Videos

Ihab Al Kabary, H. Schuldt
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引用次数: 10

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.
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运动视频中基于草图的运动查询
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。
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