Open-world computer vision by detecting and tracking hierarchical objects

通过检测和跟踪分层对象来实现开放世界计算机视觉

• 批准号: DE240100967
• 负责人: Dr Jack Valmadre
• 金额: $ 25.41万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE240100967
• 关键词: Open; world; computer; vision; detecting

This project examines the problem of detecting and tracking objects using computer vision. A fundamental limitation of current algorithms is that they require labelled training data for every object class and therefore cannot be trusted to operate in unconstrained environments. This project aims to address this limitation using novel techniques that incorporate hierarchical relationships between object classes. Expected outcomes include new paradigms for algorithm design and evaluation, and establishing the problem as a focus of international research. The key practical benefit would be to accelerate the wider deployment of visual perception in applications such as autonomous vehicles, interactive robotics, and video analysis.

这个项目研究了使用计算机视觉检测和跟踪物体的问题。当前算法的一个基本限制是，它们需要为每个对象类标记训练数据，因此不能信任在无约束环境中运行。这个项目的目的是解决这个限制，使用新的技术，将对象类之间的层次关系。预期成果包括算法设计和评估的新范例，并将该问题确立为国际研究的焦点。关键的实际好处将是加速视觉感知在自动驾驶汽车、交互式机器人和视频分析等应用中的更广泛部署。