The Analysis of Optic Flow without Locally Smooth Velocity

无局部平滑速度的光流分析

• 批准号: 8908512
• 负责人: George Andersen
• 金额: $ 6.9万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-09-01 至 1991-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8908512&HistoricalAwards=false
• 关键词: Analysis; Optic; Flow; without; Locally

Most current models of how people perceive the 3-D shape of moving objects are capable of determining shape when only a single object is present. However, in the real world we usually encounter scenes in which many objects are moving. This research will develop a new model of the perception of the shape of objects when several objects are moving in a scene. The research will study scenes in which overlapping objects cannot be distinguished in a static view, but can be distinguished when the observer or the objects are in motion. Three sets of experiments will determine the limitations of human observers in perceiving multiple moving objects. The first set of experiments will study people's ability to determine the number of objects that are moving in a complex scene. The second set of experiments will study how people identify the shapes of objects moving in a scene. The third set of experiments will study how people judge the amount of depth between objects in the scene. These results will facilitate the three-stage development of the model. The first stage will use results from the first set of experiments to derive mathematically the number of independent objects that are moving in a computer-generated scene. The second stage will use results from the second set of experiments to describe mathematically the shape of small regions of each object. The third stage will use results from the third set of experiments to specify a quantitative value of the distance between objects in a scene. An understanding of how the visual system determines the shape and depth of multiple moving objects will have important implications for the design of computer-generated displays used to train pilots, for the development of visual aids for the blind, and for the development of robotics vision systems.

当前大多数关于人们如何感知移动物体 3D 形状的模型都能够在仅存在单个物体时确定形状。 然而，在现实世界中，我们通常会遇到许多物体在移动的场景。 这项研究将开发一种新的模型，用于当多个物体在场景中移动时感知物体的形状。 该研究将研究在静态视图中无法区分重叠物体，但在观察者或物体运动时可以区分的场景。 三组实验将确定人类观察者感知多个移动物体的局限性。 第一组实验将研究人们确定复杂场景中移动物体数量的能力。 第二组实验将研究人们如何识别场景中移动物体的形状。 第三组实验将研究人们如何判断场景中物体之间的深度。 这些结果将有助于模型的三阶段开发。 第一阶段将使用第一组实验的结果从数学上推导出在计算机生成的场景中移动的独立物体的数量。 第二阶段将使用第二组实验的结果以数学方式描述每个物体的小区域的形状。 第三阶段将使用第三组实验的结果来指定场景中物体之间距离的定量值。 了解视觉系统如何确定多个移动物体的形状和深度，对于用于训练飞行员的计算机生成显示器的设计、盲人视觉辅助设备的开发以及机器人视觉系统的开发具有重要意义。