本文選題：慣性傳感器 + 虛擬現(xiàn)實(shí)��； 參考：《哈爾濱工程大學(xué)》2013年碩士論文

【摘要】：高效、便捷地獲取人體運(yùn)動(dòng)姿態(tài)信息在動(dòng)漫制作、游戲開發(fā)、影視制作等眾多領(lǐng)域具有重要的應(yīng)用價(jià)值。目前已經(jīng)取得應(yīng)用成果的人體運(yùn)動(dòng)捕捉重構(gòu)方式主要有機(jī)械式、聲學(xué)式、電磁式和光學(xué)式等，這些方式大多存在成本高、對(duì)動(dòng)作限制大和使用不方便等缺點(diǎn)。本文針對(duì)以上這些常見的運(yùn)動(dòng)捕捉重構(gòu)方式所存在的缺點(diǎn)，研究了可用于慣性傳感器的人體運(yùn)動(dòng)捕捉技術(shù)中人體運(yùn)動(dòng)模型建立的一些基本方法，設(shè)計(jì)了基于剛體動(dòng)力學(xué)的三維層次人體骨骼模型，采用基于慣性傳感器的動(dòng)作捕捉方式。這種方式具有操作方式簡(jiǎn)單、價(jià)格低廉、對(duì)環(huán)境要求低和對(duì)運(yùn)動(dòng)動(dòng)作限制小的優(yōu)點(diǎn)。 根據(jù)人體結(jié)構(gòu)和運(yùn)動(dòng)人體科學(xué)理論知識(shí)，本文設(shè)計(jì)了慣性傳感器可以在人體運(yùn)動(dòng)肢體上以任意姿態(tài)朝向綁定的姿態(tài)初始化標(biāo)定方法。通過初始化標(biāo)定時(shí)的特定動(dòng)作可以實(shí)現(xiàn)對(duì)傳感器和關(guān)節(jié)的對(duì)應(yīng)識(shí)別，并計(jì)算出各個(gè)慣性傳感器的自身坐標(biāo)系與三維人體骨骼模型中對(duì)應(yīng)的人體骨骼坐標(biāo)系的坐標(biāo)轉(zhuǎn)換關(guān)系。然后通過各個(gè)慣性傳感器姿態(tài)坐標(biāo)系的坐標(biāo)轉(zhuǎn)換和對(duì)人體骨骼樹進(jìn)行深度優(yōu)先遍歷計(jì)算，，完成人體運(yùn)動(dòng)肢體姿態(tài)數(shù)據(jù)的實(shí)時(shí)更新，驅(qū)動(dòng)人體骨骼模型模擬人體動(dòng)作，實(shí)現(xiàn)了對(duì)動(dòng)作的實(shí)時(shí)捕獲跟蹤。 在計(jì)算機(jī)三維虛擬場(chǎng)景中重構(gòu)人體運(yùn)動(dòng)姿態(tài)需要繪制三維人體模型，為了使得整個(gè)動(dòng)作捕捉系統(tǒng)具有更為廣泛的應(yīng)用前景，本文選擇了微軟公司提供的適用于Windows平臺(tái)的Direct3D圖形繪制接口。通過X文件加載網(wǎng)格模型數(shù)據(jù)中的骨骼蒙皮信息和骨骼層次信息，在進(jìn)行動(dòng)作跟蹤時(shí)根據(jù)慣性傳感器捕獲到的骨骼姿態(tài)角數(shù)據(jù)實(shí)時(shí)更新人體模型中的骨骼變換矩陣信息，以此確定人體各個(gè)骨骼的位置和朝向，實(shí)現(xiàn)了三維人體骨骼蒙皮動(dòng)畫。 為了能夠最大限度地減少動(dòng)作捕捉裝置對(duì)人體運(yùn)動(dòng)動(dòng)作的限制，本文采用了無線數(shù)據(jù)傳輸方式，并制定了慣性傳感器與上位機(jī)之間的數(shù)據(jù)通信格式。為了能夠方便地對(duì)大量運(yùn)動(dòng)數(shù)據(jù)進(jìn)行統(tǒng)計(jì)和分析，本文結(jié)合目前軟件開發(fā)常用的MySQL開源數(shù)據(jù)庫，設(shè)計(jì)了人體運(yùn)動(dòng)姿態(tài)數(shù)據(jù)庫。將采集到的實(shí)時(shí)人體姿態(tài)數(shù)據(jù)存入數(shù)據(jù)庫后，可進(jìn)一步用于人體健康、生物力學(xué)、動(dòng)作預(yù)測(cè)和行為識(shí)別等科學(xué)研究。各個(gè)慣性傳感器采集到人體運(yùn)動(dòng)肢體姿態(tài)數(shù)據(jù)后將數(shù)據(jù)傳輸?shù)絇C終端機(jī)，PC終端機(jī)上的上位機(jī)軟件實(shí)現(xiàn)了對(duì)人體運(yùn)動(dòng)姿態(tài)的三維重構(gòu)。從三維重構(gòu)結(jié)果來看，人體運(yùn)動(dòng)動(dòng)作跟蹤實(shí)時(shí)性良好，動(dòng)作重構(gòu)效果逼真。
[Abstract]:It has important application value in many fields such as animation production, game development, film production and so on. At present, the main methods of human motion capture and reconstruction have been obtained, such as mechanical, acoustic, electromagnetic and optical. Most of these methods have the disadvantages of high cost, large restrictions on movement and inconvenient use. In view of the shortcomings of these common motion capture and reconstruction methods mentioned above, this paper studies some basic methods for the establishment of human motion model, which can be used in human motion capture technology for inertial sensors. A three-dimensional hierarchical human skeleton model based on rigid body dynamics was designed, and the motion capture method based on inertial sensor was adopted. This method has the advantages of simple operation, low price, low requirement to environment and small restriction on movement. Based on the scientific knowledge of human body structure and motion human body, this paper designs an initialized calibration method in which the inertial sensor can bind in any attitude direction on the human body moving limb. By initializing the specific action of calibration, the corresponding recognition of sensors and joints can be realized, and the coordinate transformation relationship between each inertial sensor's own coordinate system and the corresponding human skeleton coordinate system in three-dimensional human skeleton model can be calculated. Then through the coordinate transformation of each inertial sensor attitude coordinate system and the depth first traversal calculation of the human skeleton tree, the real-time update of the human body motion limb posture data is completed, and the human skeleton model is driven to simulate the human body action. The real-time capture and tracking of the action is realized. In order to make the whole motion capture system have a more extensive application prospect, it is necessary to draw a three-dimensional human body model in order to reconstruct the human motion posture in the computer 3D virtual scene. In this paper, we choose the Direct3D graphic drawing interface for Windows platform provided by Microsoft. By loading the skeleton skin information and skeleton level information from the mesh model data in the X file, the skeleton transformation matrix information in the human body model can be updated in real time according to the skeletal attitude angle data captured by the inertial sensor in the course of motion tracking. In order to determine the position and orientation of each human skeleton, a three-dimensional human skeleton skin animation is realized. In order to minimize the limitation of motion capture device on human motion, this paper adopts wireless data transmission mode, and formulates the data communication format between inertial sensor and upper computer. In order to make statistics and analysis of a large number of motion data conveniently, this paper designs a human motion posture database based on MySQL open source database, which is commonly used in software development. The collected real-time human posture data can be used in human health, biomechanics, motion prediction and behavior recognition. After each inertial sensor collects the human body motion limb posture data, the data is transmitted to the PC terminal PC terminal computer software to realize the 3D reconstruction of the human body motion posture. From the result of three-dimensional reconstruction, the real-time motion tracking of human body is good, and the effect of motion reconstruction is lifelike.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.9;TP212

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 侯文生;戴加滿;鄭小林;楊琴;吳小鷹;許蓉;;基于加速度傳感器的前臂運(yùn)動(dòng)姿態(tài)檢測(cè)[J];傳感器與微系統(tǒng);2009年01期

2 崔敏;馬鐵華;段精婧;范錦彪;;基于磁強(qiáng)計(jì)和陀螺的彈箭飛行姿態(tài)測(cè)試方法[J];彈箭與制導(dǎo)學(xué)報(bào);2010年06期

3 韓曉玲;;虛擬現(xiàn)實(shí)技術(shù)發(fā)展趨向淺析[J];電腦知識(shí)與技術(shù)(學(xué)術(shù)交流);2007年02期

4 呂強(qiáng);劉峰;王珂珂;王東來;;三軸慣性傳感器ADIS16355在姿態(tài)檢測(cè)中的應(yīng)用[J];單片機(jī)與嵌入式系統(tǒng)應(yīng)用;2010年09期

5 傅建國(guó),王孝通,金良安,馬野;一種基于地球重力場(chǎng)和磁場(chǎng)的姿態(tài)估計(jì)新算法[J];電子學(xué)報(bào);2005年03期

6 李爽;羅志增;孟明;;基于加速度傳感器的下肢運(yùn)動(dòng)信息獲取方法[J];機(jī)電工程;2009年01期

7 張金劍,陳福民;光學(xué)動(dòng)作捕捉中的攝像機(jī)標(biāo)定[J];計(jì)算機(jī)應(yīng)用;2004年S1期

8 殷俊;張凱;崔晉;鄭潔;;游戲動(dòng)畫中的動(dòng)作捕捉[J];江蘇大學(xué)學(xué)報(bào)(自然科學(xué)版);2006年05期

9 李春霞,楊克儉,李波;人體骨架模型的建立及IK問題的一種解決方式[J];武漢理工大學(xué)學(xué)報(bào)(交通科學(xué)與工程版);2003年06期

10 樊翠;王麗芳;;基于D3D的三維游戲引擎的設(shè)計(jì)與實(shí)現(xiàn)[J];科學(xué)技術(shù)與工程;2006年10期

本文編號(hào)：1910351