一種三維剛體運(yùn)動(dòng)參數(shù)魯棒估計(jì)的神經(jīng)算法
A NEURAL ALGORITHM FOR ESTIMATING THE 3D RIGID BODIESMOTION PARAMETERS
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摘要: 該文提出一種基于特征點(diǎn)匹配的剛體運(yùn)動(dòng)參數(shù)估計(jì)方法。在運(yùn)動(dòng)估計(jì)線性算法的基礎(chǔ)上,文中利用全最小二乘(TLS)方法來(lái)進(jìn)行求解,并建立次分量提取神經(jīng)元來(lái)獲得該全最小二乘解?；跍y(cè)量數(shù)據(jù)中出格點(diǎn)(Outlier)的存在,我們?cè)谏窠?jīng)元的權(quán)值學(xué)習(xí)規(guī)則中引入魯棒估計(jì)思想。實(shí)驗(yàn)結(jié)果表明,該方法能有效地克服出格點(diǎn)產(chǎn)生的誤差,準(zhǔn)確地估計(jì)出剛體的三維運(yùn)動(dòng)參數(shù),比較令人滿意。Abstract: This paper deals with estimating the rigid bodiesmotion parameters from token correspondence between two perspective views.Total least square(TLS)method is used to solve the linear equations of motion estimation.Then a minor component analysis (MCA)neuron is constructed to get the TLS solution.Finally a outline resisting version of the learning rule is developed by using the statistical approach.Comparative experiments have been made and results show that our robust rules improve the performance significantly when outliers are presented.
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