On snapping up semantics of dynamic pixels from moving cameras

从移动摄像机中捕捉动态像素的语义

• 批准号: FL170100117
• 负责人: Prof Dacheng Tao
• 金额: $ 226.22万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Australian Laureate Fellowships
• 财政年份: 2018
• 资助国家: 澳大利亚
• 起止时间: 2018-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FL170100117
• 关键词: snapping; up; semantics; dynamic; pixels

The project aims to develop a suite of original models and algorithms for processing and understanding videos captured by moving cameras, and to establish the mathematical foundations for deep learning-based computer vision to provide theoretical underpinnings. The project expects to generate new knowledge that will transform moving-camera computer vision with step-changes in visual quality enhancement, compression and acceleration technologies, and solutions for fundamental computer vision tasks. A new concept of feature complexity for measuring the discriminant and learnable abilities of features from deep models will also be defined. The outcomes of the project will be critical for enabling autonomous machines to perceive and interact with the environment.

该项目旨在开发一套原始模型和算法，用于处理和理解移动摄像机捕获的视频，并为基于深度学习的计算机视觉建立数学基础，为理论基础提供支持。该项目预计将产生新的知识，将通过视觉质量增强，压缩和加速技术以及基本计算机视觉任务的解决方案的逐步变化来改变移动相机计算机视觉。还将定义一个新的特征复杂度概念，用于测量来自深度模型的特征的判别和可学习能力。该项目的成果对于使自主机器能够感知环境并与环境互动至关重要。