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Intelligent outdoor video advertisement recommendation system based on analysis of audiences' characteristics

机译:基于受众特征分析的智能户外视频广告推荐系统

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摘要

An integrated implementation framework of an intelligent recommendation system for outdoor video advertising is proposed,which is based on the analysis of audiences' characteristics.Firstly,the images of the scene and the people who view the video advertisements are captured by the network camera deployed on the video advertising terminal side.Then audiences' characteristics can be obtained by applying computer vision technologies:face detection,face tracking,gender recognition and age estimation.Finally,an intelligent recommendation algorithm is designed to decide the most fitting video ads for each terminal according to multi-dimensional statistical information of its audiences' characteristics.The experimental results show that the proposed system can effectively improve the audience arrival rate of the video advertisements by an average growth of 27.04%.Moreover,a novel face detection method and a new face tracking method have been proposed to meet the practical requirements of the system,of which the average F1-score is 0.988 and 0.951 respectively.

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  • 来源
    《高技术通讯(英文版)》 |2016年第2期|215-223|共9页
  • 作者单位

    Haikou Laboratory, Institute of Acoustics, Chinese Academy of Sciences, Haikou 570105, P.R.China;

    National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, P.R.China;

    Haikou Laboratory, Institute of Acoustics, Chinese Academy of Sciences, Haikou 570105, P.R.China;

    National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, P.R.China;

    National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, P.R.China;

    National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, P.R.China;

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  • 正文语种 eng
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  • 入库时间 2022-08-19 03:39:27
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