Statistical Methods of Model Fitting and Segmentation in Computer Vision

计算机视觉中模型拟合和分割的统计方法

• 批准号: DP0878801
• 负责人: Prof David Suter
• 金额: $ 29.48万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-08-07 至 2011-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0878801
• 关键词: Statistical; Methods; Model; Fitting; Segmentation

Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc.

电子传感器，如相机和激光器，可以提供有关我们周围物体的位置，形状和运动的丰富信息。然而，以可靠、自动和准确的方式提取这些信息需要复杂的统计理论。示例应用包括：视频监控（更好地自动检测移动的人和车辆，并描述这些人和车辆正在做什么），工业原型设计和检测（测量物体的大小和形状），城市规划（激光扫描街景以创建城市的计算机模型），娱乐业（电影特效和游戏）等。