Information fusion in content based image retrieval: A comprehensive overview
Information fusion in content based image retrieval: A comprehensive overview
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DOI：
10.1016/j.inffus.2017.01.003
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发表时间：
2017-09
期刊：
影响因子：
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通讯作者：
Luca Piras;G. Giacinto
中科院分区：
文献类型：
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作者：
Luca Piras;G. Giacinto
由于智能手机上功能强大的相机的廉价可用性以及存储空间的廉价可用性，人与人之间的交流越来越多地涉及图片的使用。 Facebook、Twitter、Instagram 等社交网络应用程序以及 WhatsApp、WeChat 等即时通讯应用程序的日益普及，就是这种现象的明显证据，因为有机会实时共享每个人所生活的环境的图像表示。媒体迅速利用了这种现象，使用同一渠道发布报道，或通过用户社区收集有关事件的其他信息。虽然图像的实时使用是通过与图像相关的元数据（即时间戳、地理位置、标签等）进行管理的，但从档案中检索图像可能绝非易事，因为图像具有丰富的语义内容，超出了其元数据提供的描述。事实证明，经过 20 多年的基于内容的图像检索 (CBIR) 研究，数字格式可用图像的数量和种类的巨大增长正在给研究界带来挑战。很容易看出，任何旨在应对此类挑战的方法都必须依赖于不同的图像表示，这些表示需要方便地融合，以适应图像语义的主观性。本文介绍了 CBIR 系统设计方案应包含的主要信息融合要素，以满足用户的苛刻需求。
An ever increasing part of communication between persons involve the use of pictures, due to the cheap availability of powerful cameras on smartphones, and the cheap availability of storage space. The rising popularity of social networking applications such as Facebook, Twitter, Instagram, and of instant messaging applications, such as WhatsApp, WeChat, is the clear evidence of this phenomenon, due to the opportunity of sharing in real-time a pictorial representation of the context each individual is living in. The media rapidly exploited this phenomenon, using the same channel, either to publish their reports, or to gather additional information on an event through the community of users. While the real-time use of images is managed through metadata associated with the image (i.e., the timestamp, the geolocation, tags, etc.), their retrieval from an archive might be far from trivial, as an image bears a rich semantic content that goes beyond the description provided by its metadata. It turns out that after more than 20 years of research on Content-Based Image Retrieval (CBIR), the giant increase in the number and variety of images available in digital format is challenging the research community. It is quite easy to see that any approach aiming at facing such challenges must rely on different image representations that need to be conveniently fused in order to adapt to the subjectivity of image semantics. This paper offers a journey through the main information fusion ingredients that a recipe for the design of a CBIR system should include to meet the demanding needs of users.