發(fā)布時間：2018-04-16 18:56

  本文選題：MEMS慣性傳感器 + 運動跟蹤　； 參考：《南京理工大學(xué)》2017年碩士論文

【摘要】：航天測發(fā)任務(wù)是一項高風(fēng)險,高投資的復(fù)雜系統(tǒng)工程,在測試過程中對試驗場操作人員的現(xiàn)場操作能力要求較高。虛擬現(xiàn)實技術(shù)作為信息傳遞與交流的手段,為測發(fā)任務(wù)提供虛擬環(huán)境,操作人員可以通過驅(qū)動虛擬手在虛擬環(huán)境中完成檢測任務(wù),以此提高操作效率。論文以航天測發(fā)任務(wù)為研究背景,主要研究基于MEMS慣性傳感器的手部跟蹤技術(shù),實現(xiàn)手勢識別以及語義交互的設(shè)計。為實現(xiàn)虛擬手的運動跟蹤,開發(fā)了一套基于慣性傳感器的手部運動跟蹤系統(tǒng)。通過分析人手的骨骼結(jié)構(gòu)和運動特性,構(gòu)建了三維手部骨骼模型。對手部初始姿態(tài)進(jìn)行標(biāo)定,將傳感器坐標(biāo)系轉(zhuǎn)換到手部骨骼坐標(biāo)系,并提出了一種手部骨骼比例的推算方法,使虛擬手更加真實。通過基于運動學(xué)的虛擬手位置解算,實現(xiàn)了手部運動的實時跟蹤。對設(shè)計的典型手勢進(jìn)行數(shù)據(jù)采集,提取行為特征來表示手勢,通過主成分分析法對手勢特征數(shù)據(jù)進(jìn)行降維,應(yīng)用網(wǎng)格搜索和5折交叉驗證的SVM分類算法。針對分類算法,分別使用多項式核函數(shù),徑向基核函數(shù)以及組合核函數(shù)對比識別率,選取最優(yōu)的核函數(shù),實現(xiàn)手勢識別。為實現(xiàn)航天測發(fā)任務(wù)中的交互研究,采用隱馬爾可夫模型對手部動作序列識別。面向特定場景設(shè)計了虛擬手的語義交互過程,并在場景中進(jìn)行驗證。論文的研究成果在航天發(fā)射任務(wù)仿真虛擬環(huán)境中得到應(yīng)用驗證。
[Abstract]:The mission of spaceflight testing is a complex system engineering with high risk and high investment.Virtual reality technology, as a means of information transmission and communication, provides a virtual environment for testing and sending tasks, and the operator can improve the operation efficiency by driving virtual hands to complete the detection tasks in the virtual environment.Based on the research background of spaceflight hair testing task, this paper mainly studies the hand tracking technology based on MEMS inertial sensor, realizes the design of gesture recognition and semantic interaction.In order to realize the motion tracking of virtual hand, a hand motion tracking system based on inertial sensor is developed.By analyzing the skeletal structure and motion characteristics of human hand, a three-dimensional hand bone model was constructed.The initial attitude of the hand is calibrated, the sensor coordinate system is converted to the skeletal coordinate system of the hand, and a method of calculating the ratio of the hand bone is proposed to make the virtual hand more realistic.The real-time tracking of hand motion is realized by solving the position of virtual hand based on kinematics.The typical gestures are collected and the behavior features are extracted to represent the gestures. The dimensionality of gesture features is reduced by principal component analysis (PCA), and the SVM classification algorithm based on grid search and 5 fold cross-validation is applied.For the classification algorithm, the polynomial kernel function, the radial basis kernel function and the combined kernel function are used to compare the recognition rate, and the optimal kernel function is selected to realize gesture recognition.In order to realize the interactive research of spaceflight mission, Hidden Markov Model (hmm) is used to recognize the hand motion sequence.The semantic interaction process of virtual hand is designed for specific scene and verified in the scene.The research results of this paper have been applied to the simulation virtual environment of space launch mission.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：V55;TP391.9

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本文編號：1760182