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The Best Practice of University and Community Cooperation in Open Source Software Project - TV Station Media Images Query System for Example

机译:开源软件项目中大学与社区合作的最佳实践-以电视台媒体图像查询系统为例

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摘要

One open source software project, Open Source Technology Development and Cultivation of Talent, of Institute for Information Industry (III), Taiwan released an opportunity and gave us a valuable practice in helping some engineers, students, and teachers to work together. In this project, we try to develop the TV station media images query system prototype. Face recognition based on videos or image sets has been involved in the project. We try to apply Convolutional Neural Networks (CNN) and perform feature extraction on a target face in multiple image frames of given videos and generate multiple face feature vectors respectively. This proposed prototype and flowchart try to convert the plurality of face feature vectors into a feature vector of a predetermined dimension and judge the feature vector of the predetermined dimension by using a classifier to recognize the target face. The user can input Chinese name of actress and pressure search button, then, if information retrieved from the database associated with a selected person, it can show all similar images and time associated with a given face name.
机译:台湾信息产业研究所(III)的一个开源软件项目“开源技术开发与人才培养”释放了机会,并为我们提供了宝贵的实践经验,可以帮助一些工程师,学生和教师一起工作。在这个项目中,我们尝试开发电视台媒体图像查询系统的原型。该项目涉及基于视频或图像集的面部识别。我们尝试应用卷积神经网络(CNN),并在给定视频的多个图像帧中对目标面部进行特征提取,并分别生成多个面部特征向量。该提出的原型和流程图试图通过使用分类器识别目标面部来将多个面部特征向量转换为预定维度的特征向量并判断该预定维度的特征向量。用户可以输入女演员的中文名称和压力搜索按钮,然后,如果从与所选人物相关联的数据库中检索到的信息可以显示与给定面孔名称相关联的所有相似图像和时间。

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