Multimedia Retrieval in Mixed Reality: Leveraging Live Queries for Immersive Experiences

Rahel Arnold, H. Schuldt
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Abstract

Recent advancements in Mixed Reality (MR) technology and the exponential growth of multimedia data production have led to the emergence of innovative approaches for efficient content retrieval. This paper introduces Mixed Reality Multimedia Retrieval ((MR)2), a groundbreaking concept at the convergence of MR and multimedia retrieval. At its core, (MR)2 leverages MR’s transformative capabilities with an innovative live query option, allowing users to initiate queries intuitively through real-world object interactions. By autonomously generating queries based on object recognition in the user’s field of view, (MR)2 facilitates the retrieval of similar multimedia content from a connected database. The technical backbone of the (MR)2 framework includes object detection (YOLOv8), semantic similarity search (CLIP), and data management (Cottontail DB). Our research redefines user interactions with multimedia databases, seamlessly bridging the physical and digital domains. A successful iOS prototype application demonstrates promising results, paving the way for immersive and context-aware multimedia retrieval in the MR era.
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混合现实中的多媒体检索:利用实时查询实现沉浸式体验
混合现实(MR)技术的最新进展和多媒体数据生产的指数级增长,导致了高效内容检索创新方法的出现。本文介绍了混合现实多媒体检索((MR)2),这是一个突破性的概念,是混合现实和多媒体检索的融合。(MR)2的核心是利用MR的变革能力和创新的实时查询选项,允许用户通过现实世界中的对象交互直观地发起查询。通过根据用户视野中的物体识别自主生成查询,(MR)2 可以帮助用户从连接的数据库中检索类似的多媒体内容。(MR)2 框架的技术骨干包括对象检测(YOLOv8)、语义相似性搜索(CLIP)和数据管理(Cottontail DB)。我们的研究重新定义了用户与多媒体数据库的交互,无缝连接了物理和数字领域。一个成功的 iOS 原型应用展示了可喜的成果,为磁共振时代的沉浸式和上下文感知多媒体检索铺平了道路。
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