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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >ARTIFICIAL INTELLIGENCE AS A LOW-COST SOLUTION FOR MUSEUM VISITDIGITAL CONTENT ENRICHMENT: THE CASE OF THE FOLKLORE MUSEUM OFXANTHI
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ARTIFICIAL INTELLIGENCE AS A LOW-COST SOLUTION FOR MUSEUM VISITDIGITAL CONTENT ENRICHMENT: THE CASE OF THE FOLKLORE MUSEUM OFXANTHI

机译：人工智能作为博物馆访问博物馆内容丰富的低成本解决方案：Xanthi民间传说博物馆的案例

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The on-demand content enrichment of an exhibition center visit is an active applied research domain. This work focuses on the exploitation of mobile devices as an efficient medium to deliver information related to an exhibit or an area within the exhibition center by utilizing machine learning approaches. We present YPOPSEI, an integrated system that formulates the information retrieval task as an image recognition mechanism, enabling visitors to simply capture an entity of interest in order to acquire information similar to a tour-guidance experience via their personal mobile devices. This scheme not only minimizes the additional infrastructure requirements, but additionally enhances the versatility in cases of exhibits topology alterations while still providing high accuracy in terms of image content recognition. Two hybrid approaches are developed that set Convolutional Neural Networks (CNNs) and Bags of VisualWords (BOVWs) to operate in a synergistic and cooperative manner. They are evaluated under real-world conditions on a client-server Web architecture system that experimentally operates within the premises of the Folklore Museum of Xanthi, Greece.
机译：展览中心访问的按需内容丰富是一个活跃的应用研究领域。这项工作侧重于移动设备的开发作为一种有效的媒介，以通过利用机器学习方法提供与展览中心内的展览中心或区域相关的信息。我们呈现YPOPSEI，该集成系统将信息检索任务作为图像识别机制，使访问者能够简单地捕获感兴趣的实体，以便通过他们的个人移动设备获取类似于旅游指导体验的信息。该方案不仅最大限度地减少了额外的基础设施要求，而且还增强了在展示拓扑改造的情况下的多功能性，同时在图像内容识别方面提供高精度。开发了两种混合方法，将卷积神经网络（CNNS）和视觉签字（BOVW）的袋子以协同合作的方式操作。它们根据客户 - 服务器Web架构系统的真实条件进行评估，该系统在经过实验运行的希腊Xanthi Xanthi博物馆的房屋内。

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