数据驱动vs.语义技术驱动的基于标签的视频位置估计

Jaeyoung Choi, G. Friedland
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引用次数: 1

摘要

下面的文章描述了基于文本元数据确定Flickr视频记录地点地理坐标的两种方法。该系统在MediaEval 2010放置任务评估数据上进行了测试,该数据由5091个未经过滤的测试视频和元数据记录组成。第一个系统是数据驱动的方法,它使用基于标记空间方差的启发式方法。第二种方法通过使用语义技术(如扩展的Word net和地理地名词典)扩展了这种启发式方法。性能的峰值是能够将14%的视频分类到精度在10米以内。本文介绍了这两种算法,评估了它们的准确性,并讨论了使用语义技术进行此任务的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Driven vs. Semantic-Technology-Driven Tag-Based Video Location Estimation
The following article describes two approaches to determining the geo-coordinates of the recording place of Flickr videos based on textual metadata. The systems are tested on the MediaEval 2010 Placing Task evaluation data, which consists of 5091 unfiltered test videos and metadata records. The first system is a data-driven approach that uses a heuristics based on the spatial variance of tags. The second one extends this heuristics by using semantic technologies, such as extended Word net and a geographical gazetteer. The performance peaks at being able to classify 14% of the videos to within an accuracy of 10m. The article present the two algorithms, evaluates their accuracy and discusses the advantages and disadvantages of using Semantic technologies for this task.
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