Generating Facial Composites from Principal Components
نویسندگان
چکیده
منابع مشابه
Generating market risk scenarios using principal components analysis
In this paper, I study a number of statistical issues that arise in the formulation of stress scenarios for market risk in financial instruments. The possibility of reducing the number of scenarios through the use of data-based, statistical dimension reduction methods is explored. Using data on returns to spot exchange, stock market and interest rate products for a number of countries, I show t...
متن کاملInitial Results of Multilevel Principal Components Analysis of Facial Shape
Traditionally, active shape models (ASMs) do not make a distinction between groups in the subject population and they rely on methods such as (single-level) principal components analysis (PCA). Multilevel principal components analysis (PCA) allows one to model betweengroup effects and within-group effects explicitly. Three dimensional (3D) laser scans were taken from 240 subjects (38 Croatian f...
متن کاملFACES Evolving faces from principal components
A system that uses an underlying genetic algorithm to evolve faces in response to user selection is described. The descriptions of faces used by the system are derived from a statistical analysis of a set of faces. The faces used for generation are transformed to an average shape by defining locations around each face and morphing. The shape-free images and shape vectors are then separately sub...
متن کاملDetecting influential observations in principal components and common principal components
Detecting outlying observations is an important step in any analysis, even when robust estimates are used. In particular, the robustified Mahalanobis distance is a natural measure of outlyingness if one focuses on ellipsoidal distributions. However, it is well known that the asymptotic chi-square approximation for the cutoff value of the Mahalanobis distance based on several robust estimates (l...
متن کاملPersian Handwriting Analysis Using Functional Principal Components
Principal components analysis is a well-known statistical method in dealing with large dependent data sets. It is also used in functional data for both purposes of data reduction as well as variation representation. On the other hand "handwriting" is one of the objects, studied in various statistical fields like pattern recognition and shape analysis. Considering time as the argument,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: MATEC Web of Conferences
سال: 2016
ISSN: 2261-236X
DOI: 10.1051/matecconf/20164204006