Vision and Sensing of Human Motion for Athletes and Artists

生物识别通常是指将模式识别方法应用于出于安全目的而对人体进行测量。通过将各种信号处理和计算机视觉技术应用于人体运动的测量和分析，以应用于田径和步态障碍的临床治疗，我们有更广阔的视野。典型的应用程序是运动员在跑步机上跑步，但经历了疼痛。我们知道，如果运动员以不同的方式跑步，我们可以消除疼痛，但步态不容易改变。以这样的田径项目为例，我们寻求开发测量和分析人体运动的算法和系统，以便向该人实时产生反馈。一个可行的假设是，适当设计的反馈将是纠正步态的有效方法。我们已经在之前的工作中用一个系统演示了这个概念，该系统旨在纠正失去交叉能力的速滑运动员的技术。我们专注于音频反馈，因为为了运动员的安全，它让眼睛自由活动，也因为我们知道，人们可以协调他们的动作和声音。这项拟议的研究建立在以前成功的基础上，通过探索使用各种传感器来测量运动(计算机视觉、运动捕捉和安装在运动员身上的传感器)，在各种环境(速度滑冰椭圆形、跑步机、跑道、人行道)中进行测量，开发与各种传感器和运动同步的信号处理算法，检查各种运动模式(行走、跑步、滑冰)，并开发和测试针对各种预期结果(运动成绩、临床治疗)的算法和系统。 我们方法的一个关键部分是与艺术家和音乐家接触。虽然艺术家和音乐家可以利用我们的技术进步来促进他们的审美目标，但我们的科学工作也会收到互惠的好处，因为他们有助于设计音频和视觉反馈，从而有效地从运动员那里获得所需的反应。

Biometrics typically refer to the application of pattern recognition methods to the measurement of humans for security purposes. We take a broader view, by applying a variety of signal processing and computer vision techniques to the measurement and analysis of human motion, for applications in athletics and clinical treatment of gait disorders. The prototypical application is an athlete running on a treadmill, but experiencing pain. We know that if the athlete runs differently, we can eliminate the pain, but gaits are not easily altered. Using athletics such as this as a case study, we seek to develop algorithms and systems that measure and analyze human motion to produce feedback to that person in real-time. A working hypothesis is that properly designed feedback will be an effective way to correct a gait. We have demonstrated the concept in previous work with a system designed to correct the technique of a speed skater who had lost his ability to do cross overs. We focus on audio feedback because it leaves the eyes free for the athlete's safety, and because we know that people can coordinate their movements with sound. The proposed research builds on this previous success by exploring the use of various sensors to measure locomotion (computer vision, motion capture, and sensors mounted on the athlete), measuring in a variety of settings (speed skating oval, treadmill, running track, sidewalk), developing signal processing algorithms for synchronization with the various sensors and motions, examining a variety of modes of locomotion (walking, running, skating), and developing and testing algorithms and systems that target a variety of desired outcomes (athletic performance, clinical treatment). A key part of our methodology is to engage with artists and musicians. While artists and musicians can use our technological advances to further their aesthetic goals, our scientific work receives a reciprocal benefit as they contribute to the design of audio and visual feedback that is effective in obtaining the desired response from an athlete.