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Proceedings of the 51st ACM Southeast Conference最新文献

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Exploiting Sound Latency Using Low-level Affective Video Features in Amateur Video 利用业余视频中的低级情感视频特征开发声音延迟
Pub Date : 2013-04-04 DOI: 10.1145/2498328.2659439
J. French
The increased availability of multimedia equipment has resulted in large repositories of publically available, amateur videos. Users need to be able to identify and retrieve videos that contain content of interest. Automated methods are desirable, as manual content discovery is tedious. One of the more difficult challenges in video indexing is affective video indexing, which focuses on content that is intended to evoke certain emotions in users. Without pre-determined cinematographic cues, indexing strategies applied to amateur videos must rely on the exploration and analysis of low-level characteristics such as sound energy and motion. This study focuses on (1) improving the existing method for correctly identifying target affective content, and (2) exploiting sound latency in correlation to object motion in amateur videos containing slapstick, one of the most popular humor techniques. By utilizing low-level video characteristics, the identification of the targeted content can be performed without relying on the emotional responses of humans.
多媒体设备可用性的增加导致了大量可公开获得的业余录像带的存储。用户需要能够识别和检索视频,其中包含感兴趣的内容。自动化的方法是可取的,因为手工的内容发现是乏味的。视频索引中比较困难的挑战之一是情感视频索引,它关注的是旨在唤起用户某种情感的内容。没有预先确定的电影线索,应用于业余视频的索引策略必须依赖于对低水平特征(如声音能量和运动)的探索和分析。本研究的重点是:(1)改进现有的正确识别目标情感内容的方法;(2)在包含打诨的业余视频中利用与物体运动相关的声音延迟,这是最流行的幽默技巧之一。通过利用低级视频特征,可以在不依赖人类情绪反应的情况下进行目标内容的识别。
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Proceedings of the 51st ACM Southeast Conference
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