QUEMAT: QUEry-adaptive Media Asset Tracking
QUEMAT:查询自适应媒体资产跟踪
基本信息
- 批准号:104408
- 负责人:
- 金额:$ 36.45万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Collaborative R&D
- 财政年份:2018
- 资助国家:英国
- 起止时间:2018 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
FOCAL International (FOCAL) is the leading global trade association facilitating use of commercial footage and other content in all forms of media production, with over 300 international members comprising content libraries, archives, production researchers and service providers. The company has offered a popular "Footage Finder" service for many years, generating sales leads and routing these to members. The QUEMAT project creates novel deep learning technology (via technology partners Dithen and The Media Institute) to innovate a high-impact new "Footage Finder" service, leveraging the established footprint of FOCAL International, and in turn generating an abundance of learning and training data through adoption to continuously improve the project's deep learning performance. The QUEMAT sustainable ecosystem delivers 'network effects' inside and outside the project, yielding high-precision and commercially relevant results to visual search queries within Footage Finder and across an abundance of applications.The project is ideally timed as inflection points have been reached concurrently in three disparate arenas: a) film and television production is burgeoning with new routes to market (e.g. Netflix now invest more in original production than CBS); b) deep neural network (DNN) technology has reached a level of maturity allowing investments in machine learning to deliver unprecedented returns; and c) technology to perform 'video signature extraction' (i.e., allowing for rapid search of video without the need to process pixels) has been validated by new MPEG standards activity: 'Compact Descriptors for Video Analysis' (CDVA), creating a foundation for widespread adoption.The project will innovate the novel DNN (Deep Neural Network) -based media asset processing and discovery capabilities with the following unique features: i) it will allow for the continuous production of compact signatures per query type while remaining standards-compliant; ii) it will be specifically trained to be repurposed for various query types with an automated query-driven customization stage that can be performed offline; and iii) the operational complexity will be tunable and the entire software pipeline will be portable to any public cloud provider for easy scaling and adoption across media enterprises.Overall, QUEMAT technology will deliver increased revenues to content owners and increase operational efficiencies at a time when content producers and footage libraries are struggling to reconfigure traditional value chains to benefit from new monetization opportunities. The project's three partners: FOCAL, The Media Institute and Dithen -- bringing together media industry presence and leading technology expertise in deep learning and media processing, and a record of successful collaboration.
FOCAL International (FOCAL)是全球领先的贸易协会,促进商业镜头和其他内容在各种形式的媒体制作中的使用,拥有300多个国际成员,包括内容图书馆、档案馆、制作研究人员和服务提供商。该公司多年来一直提供广受欢迎的“Footage Finder”服务,产生销售线索并将其转发给会员。QUEMAT项目创造了新颖的深度学习技术(通过技术合作伙伴Dithen和The Media Institute),以创新一种高影响力的新型“Footage Finder”服务,利用FOCAL International的现有足迹,通过采用产生丰富的学习和培训数据,不断提高项目的深度学习性能。QUEMAT可持续生态系统在项目内外提供“网络效应”,在Footage Finder和大量应用程序中为视觉搜索查询提供高精度和商业相关的结果。这个项目的时机非常理想,因为在三个不同的领域同时出现了拐点:a)电影和电视制作正在蓬勃发展,有新的市场途径(例如,Netflix现在在原创制作上的投资超过了CBS);b)深度神经网络(DNN)技术已达到成熟水平,使机器学习投资获得前所未有的回报;c)执行“视频签名提取”的技术(即允许在不需要处理像素的情况下快速搜索视频)已被新的MPEG标准活动验证:“用于视频分析的紧凑描述符”(CDVA),为广泛采用奠定了基础。该项目将创新新颖的基于深度神经网络的媒体资产处理和发现功能,具有以下独特功能:i)它将允许每个查询类型连续生成紧凑签名,同时保持标准兼容;Ii)它将经过专门的训练,以重新用于各种查询类型,具有可以离线执行的自动查询驱动的定制阶段;iii)操作复杂性将是可调的,整个软件管道将可移植到任何公共云提供商,以便轻松扩展和跨媒体企业采用。总的来说,QUEMAT技术将为内容所有者带来更多的收入,并提高运营效率,目前内容制作商和素材库正在努力重新配置传统价值链,以从新的货币化机会中获益。该项目的三个合作伙伴:FOCAL、The Media Institute和Dithen——将媒体行业的影响力与深度学习和媒体处理方面的领先技术专长结合在一起,并取得了成功的合作记录。
项目成果
期刊论文数量(0)
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专利数量(0)
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
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吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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