STRATEGIES FOR QUALITY-AWARE VIDEO CONTENT ANALYTICS

A. Reibman
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引用次数: 2

Abstract

Recent research in video analytics promises the capability to automatically detect and extract information from video. Potential tasks include object and pedestrian detection, object and face recognition, motion detection, object tracking, as well as background subtraction and activity recognition. However, in many instances, the quality of the video from which information is to be extracted is not very high. This may be because of system constraints (like a bandwidth constraint or VHS recorder), environmental conditions (fog or low light), or a poor camera (wobbly/moving camera, limited FOV, or just a low-quality lens).
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质量意识视频内容分析策略
最近在视频分析方面的研究承诺能够自动检测并从视频中提取信息。潜在的任务包括物体和行人检测,物体和人脸识别,运动检测,物体跟踪,以及背景减去和活动识别。然而,在许多情况下,要从中提取信息的视频的质量不是很高。这可能是由于系统限制(如带宽限制或VHS录像机),环境条件(雾或弱光),或不良相机(晃动/移动相机,有限的视场,或只是一个低质量的镜头)。
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