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使用步态生物识别技术对人类进行基于内容的检索

Performing Content-based Retrieval of Humans using Gait Biometrics
课程网址: http://videolectures.net/samt08_samangooei_pcbr/  
主讲教师: Sina Samangooei
开课单位: 南安普顿大学
开课时间: 2008-12-18
课程语种: 英语
中文简介:
为了分析监控视频,我们需要有效地探索包含步行人类视频的大型数据集。在该分辨率下,人类步行(他们的步态)可以比其他特征(例如脸部)更容易自动确定。分析可以依赖于使用语义注释来丰富的视频数据的检索。手动注释过程耗时且由于主题偏差而容易出错。我们使用语义查询探索基于内容的包含步行主题的视频的检索。我们使用步态来评估当前的生物识别研究,这种研究在识别远距离人群方面具有独特的优势。我们介绍了一组远距离可识别的人类特征的语义特征,概述了他们的心理有效性。在所选择的步态签名的相似性暗示某些语义特征的相似性的前提下工作,我们使用来自信息检索社区的流行的潜在语义分析技术来执行一组语义检索实验。
课程简介: In order to analyse surveillance video, we need to efficiently explore large datasets containing videos of walking humans. At this resolution, the human walk (their gait) can be determined automatically more readily than other features, such as the face. Analysis can rely retrieval of video data which has been enriched using semantic annotations. A manual annotation process is time-consuming and prone to error due to subject bias. We explore the content-based retrieval of videos containing walking subjects using semantic queries. We evaluate current biometric research using gait, unique in their effectiveness at recognising people at a distance. We introduce a set of semantic traits discernible _by humans_ at a distance, outlining their psychological validity. Working under the premise that similarity of the chosen gait signature implies similarity of certain semantic traits we perform a set of semantic retrieval experiments using popular latent semantic analysis techniques from the information retrieval community.
关 键 词: 视频数据; 语义查询; 信息检索社区
课程来源: 视频讲座网
最后编审: 2019-09-17:lxf
阅读次数: 45