基于排序和语义查询解释的图像增量学习概念交互检测

K. Schutte, H. Bouma, J. Schavemaker, L. Daniele, Maya Sappelli, G. Koot, P. Eendebak, G. Azzopardi, Martijn Spitters, M. D. Boer, M. Kruithof, Paul Brandt
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引用次数: 12

摘要

联网摄像机的数量呈指数级增长。不同领域的多种应用导致对视频传感器数据进行语义搜索的需求日益增加。在本文中,我们展示了GOOSE演示器,它是一个实时通用搜索引擎,允许用户提出自然语言查询来检索相应的图像。自顶向下,该演示器解释查询,并将查询呈现为直观的图形,以收集用户反馈。自下而上,系统自动识别和定位图像中的概念,并逐步学习新概念。智能排名将两者结合起来,并允许有效地检索相关图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation
The number of networked cameras is growing exponentially. Multiple applications in different domains result in an increasing need to search semantically over video sensor data. In this paper, we present the GOOSE demonstrator, which is a real-time general-purpose search engine that allows users to pose natural language queries to retrieve corresponding images. Top-down, this demonstrator interprets queries, which are presented as an intuitive graph to collect user feedback. Bottom-up, the system automatically recognizes and localizes concepts in images and it can incrementally learn novel concepts. A smart ranking combines both and allows effective retrieval of relevant images.
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