Semantic Vectorisation: From Bitmaps to Intelligent Representations

语义矢量化：从位图到智能表示

• 批准号: DP150104645
• 负责人: Prof Fatih Porikli
• 金额: $ 25.55万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-06-30 至 2019-03-06
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP150104645
• 关键词: Semantic; Vectorisation; Bitmaps; Intelligent; Representations

The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.

这个创新项目的目标是提供一个解决方案，以语义丰富的矢量图形表示自然图像的开放问题。面临的挑战是识别图像和视频的关键视觉和时间元素，并有效地将视觉数据分解为忠实于原始数据、紧凑且可编辑的语义向量表示。该项目旨在研究新的位图到矢量转换方法。它有望开发一个框架，语义标签和超链接可以自动嵌入到视觉数据。它希望开创一个图像网络的创建，其中链接在图像/视频区域上。预计将提供新的图像简化，风格化和非真实感渲染方法。