Motion Analysis in Biological and Computer Vision Systems

生物和计算机视觉系统中的运动分析

• 批准号: 8719394
• 负责人: Tomaso Poggio
• 金额: $ 51.54万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-06-15 至 1992-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8719394&HistoricalAwards=false
• 关键词: Motion; Analysis; Biological; Computer; Vision

The measurement and use of visual motion is a fundamental component of biological and machine vision systems that provides essential sensory information for tasks such as navigation, object manipulation and recognition. Significant advances have been made toward understanding how vision systems might solve the individual problems of detecting sudden movements, segmenting the scence into distinct objects on the basic of motion discontinuities, tracking objects of interest, recovering the three-dimensional structure and movement of object surfaces, and inferring their own movement relative to the environment. This research examines how solutions to these problems are integrated into a motion analysis that performs these functions with speed, accuracy, reliability and flexibility. Such a system must embody multiple computational strategies that combine fast and robust methods for deriving qualitative motion information with slower, accurate methods for deriving quantitative models of three- dimensional structure and motion. The approach taken in this project brings together theoretical analyses, implementation and testing of computer algorithms, and observations on human motion perception. This research will lead both to significant improvements in the performance of computer vision systems at analyzing dynamic images, and new understanding of motion analysis in the human visual system.

视觉运动的测量和使用是生物和机器视觉系统的基本组成部分，为导航、物体操纵和识别等任务提供必要的感官信息。 在理解视觉系统如何解决检测突然运动、根据运动不连续性将场景分割成不同对象、跟踪感兴趣的对象、恢复物体表面的三维结构和运动等个别问题方面已经取得了重大进展。并推断自己相对于环境的运动。 这项研究探讨了如何将这些问题的解决方案集成到运动分析中，以快速、准确、可靠和灵活地执行这些功能。 这样的系统必须体现多种计算策略，将用于导出定性运动信息的快速而稳健的方法与用于导出三维结构和运动的定量模型的较慢且准确的方法相结合。 该项目采用的方法汇集了理论分析、计算机算法的实现和测试以及对人体运动感知的观察。 这项研究将显着提高计算机视觉系统分析动态图像的性能，并带来对人类视觉系统运动分析的新理解。