New range camera models for dynamic measurement

用于动态测量的新系列相机模型

• 批准号: 355423-2013
• 负责人: Lichti, Derek
• 金额: $ 2.55万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=572573
• 关键词: New; range; camera; models; dynamic

Systems for the capture and subsequent analysis of human motion are important tools in numerous fields. Their function is to capture geometric information about a human subject performing some motion from which biomechanical parameters such as muscle and joint forces can be inferred. These are in turn used to aid in clinical diagnoses, to provide a more sound understanding of a human movement process or to improve performance. Numerous applications exist that include but are not limited to: the analysis of human gait (both normal and pathological); the design of prosthetics and orthotics; patient rehabilitation; back shape and spinal motion measurement; joint mechanics; ergonomic design; human surveillance; entertainment (gaming, movies) and sports science to improve athlete performance. Current systems used in the medical, sport and entertainment spaces require the placement of invasive markers, in the case of video camera systems, or electronic sensors (wired or wireless). These can bias the collected data and lead to incorrect conclusions due to inherent skin movement and can cause the subject to perform unnatural movements. Furthermore their installation is very time consuming. This research aims to create a new paradigm in markerless human motion measurement using 3D range camera technology. New computer processing algorithms will be developed to determine the human motion parameters from the 3D camera data without relying upon the placement of invasive markers or devices. The results will improve the ease of use of motion capture systems.

用于捕获和随后分析人体运动的系统是许多领域中的重要工具。它们的功能是捕获关于执行某些运动的人类主体的几何信息，从中可以推断出诸如肌肉和关节力的生物力学参数。这些反过来又用于辅助临床诊断，以提供对人体运动过程的更好理解或提高性能。存在许多应用，包括但不限于：人类步态（正常和病理）的分析;假肢和矫形器的设计;患者康复;背部形状和脊柱运动测量;关节力学;人体工程学设计;人类监控;娱乐（游戏，电影）和体育科学，以提高运动员的表现。 在医疗、体育和娱乐空间中使用的当前系统需要放置侵入性标记（在视频摄像机系统的情况下）或电子传感器（有线或无线）。 这些可能会使收集的数据产生偏差，并由于固有的皮肤运动而导致错误的结论，并可能导致受试者进行不自然的运动。此外，它们的安装非常耗时。本研究旨在建立一个新的范例，在无标记人体运动测量使用三维距离相机技术。将开发新的计算机处理算法，以从3D摄像机数据确定人体运动参数，而不依赖于侵入性标记或设备的放置。研究结果将提高运动捕捉系统的易用性。