Real-time image and video processing, classification, and retrieval using hardware acceleration and extremely large datasets

使用硬件加速和超大数据集进行实时图像和视频处理、分类和检索

• 批准号: 249501-2011
• 负责人: Aarabi, Parham
• 金额: $ 1.6万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=524679
• 关键词: Real; time; image; video; processing

In the past few years, we have seen an exponential increase in the amount of videos and images that have been recorded and placed on the internet. Smart mobile phones (Blackberry, iPhone, etc.) now enable seamless recording, transmission, and sharing of videos in near-real-time. Whereas just two decades ago there were a few video broadcasters and publishers, today there are millions, if not billions, of video broadcasters and online publishers. With all this visual content, how do we find what we want? How to we categorize the content? How do we develop search engines that bring order to visual content just as text-based search engines (Google, Bing, etc.) brought order to the textual web?

在过去的几年中，我们看到被记录并放置在互联网上的视频和图像的数量呈指数级增长。 智能手机（Blackberry、iPhone 等）现在可以近乎实时地无缝录制、传输和共享视频。 二十年前，只有少数视频广播公司和出版商，而如今，视频广播公司和在线出版商数量达到数百万甚至数十亿。 面对所有这些视觉内容，我们如何找到我们想要的内容？ 我们如何对内容进行分类？ 我们如何开发搜索引擎，为视觉内容带来秩序，就像基于文本的搜索引擎（Google、Bing 等）为文本网络带来秩序一样？