李艳灵, 杨志鹏, 王莎莎, 江海洋. 基于卷积神经网络进行电影院人群分布统计[J]. 信阳师范学院学报(自然科学版), 2020, 33(4): 675-680. DOI: 10.3969/j.issn.1003-0972.2020.04.028
引用本文: 李艳灵, 杨志鹏, 王莎莎, 江海洋. 基于卷积神经网络进行电影院人群分布统计[J]. 信阳师范学院学报(自然科学版), 2020, 33(4): 675-680. DOI: 10.3969/j.issn.1003-0972.2020.04.028
LI Yanling, YANG Zhipeng, WANG Shasha, JIANG Haiyang. The Distribution of Cinema Population Based on Convolutional Neural Network[J]. Journal of Xinyang Normal University (Natural Science Edition), 2020, 33(4): 675-680. DOI: 10.3969/j.issn.1003-0972.2020.04.028
Citation: LI Yanling, YANG Zhipeng, WANG Shasha, JIANG Haiyang. The Distribution of Cinema Population Based on Convolutional Neural Network[J]. Journal of Xinyang Normal University (Natural Science Edition), 2020, 33(4): 675-680. DOI: 10.3969/j.issn.1003-0972.2020.04.028

基于卷积神经网络进行电影院人群分布统计

The Distribution of Cinema Population Based on Convolutional Neural Network

  • 摘要: 基于传统算法检测人脸提取特征来预测人的性别和年龄,构建一种基于卷积神经网络(Convolutional Neural Network,CNN)的电影院人群分布统计模型.该模型包括人脸检测模型和卷积神经网络模型两部分,根据性别和年龄对人群进行精确分类,从而得到电影院人群的分布,为电影院投放电影提供可靠的依据.在Adience公开数据集上的实验结果表明:该模型对于电影院人群分布统计的准确率高达77.92%.

     

    Abstract: A cinema population distribution statistical model based on Convolutional Neural Network (CNN) is formulated by detecting facial extraction features to predict people's age and gender based on traditional algorithms. The model includes two parts:face detection model and convolution neural network model. It classifies people accurately according to age and gender, and then gets the distribution of cinema crowd, which provides a reliable basis for cinema film projection. The experimental results on adience open data set show that the accuracy of the designed model is as high as 77.92% for cinema crowd distribution statistics.

     

/

返回文章
返回