Presentation 2007-02-23
Asymptotic Efficiency of Maximum Likelihood Estimation in Face Tracking Model Identification
Xin Lu, Kiyoshi Nishiyama,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper discusses the asymptotic efficiency of the maximum likelihood estimation (MLE) when the fece tracking model is specified as vector autoregression (VAR). When the size of the data vector in VAR is enlarged a little, the asymptotic distributions of the estimates by MLE become too wide to satisfy the precision requirement. Consequently, it is necessary to largely increase the quantity of the tested data for shortening the asymptotic distributions and obtaining the suitable estimates. In this paper, we give an explanation of this phenomenon and suggest user to avoid using a very long-term MLE to obtain the estimates of VAR in large size in face tracking.
Keyword(in Japanese) (See Japanese page)
Keyword(in English)
Paper # PRMU2006-234,HIP2006-127
Date of Issue

Conference Information
Committee HIP
Conference Date 2007/2/16(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Human Information Processing (HIP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Asymptotic Efficiency of Maximum Likelihood Estimation in Face Tracking Model Identification
Sub Title (in English)
Keyword(1)
1st Author's Name Xin Lu
1st Author's Affiliation Department of Computer and Information Sciences, Faculty of Engineering, Iwate University()
2nd Author's Name Kiyoshi Nishiyama
2nd Author's Affiliation Department of Computer and Information Sciences, Faculty of Engineering, Iwate University
Date 2007-02-23
Paper # PRMU2006-234,HIP2006-127
Volume (vol) vol.106
Number (no) 541
Page pp.pp.-
#Pages 5
Date of Issue