Literature DB >> 17496382

On the dimensionality of face space.

Marsha Meytlis1, Lawrence Sirovich.   

Abstract

The dimensionality of face space is measured objectively in a psychophysical study. Within this framework, we obtain a measurement of the dimension for the human visual system. Using an eigenface basis, evidence is presented that talented human observers are able to identify familiar faces that lie in a space of roughly 100 dimensions and the average observer requires a space of between 100 and 200 dimensions. This is below most current estimates. It is further argued that these estimates give an upper bound for face space dimension and this might be lowered by better constructed "eigenfaces" and by talented observers.

Entities:  

Mesh:

Year:  2007        PMID: 17496382     DOI: 10.1109/TPAMI.2007.1033

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  8 in total

1.  Symmetry, probability, and recognition in face space.

Authors:  Lawrence Sirovich; Marsha Meytlis
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-13       Impact factor: 11.205

2.  Exploring the perceptual spaces of faces, cars and birds in children and adults.

Authors:  James W Tanaka; Tamara L Meixner; Justin Kantner
Journal:  Dev Sci       Date:  2010-12-16

3.  Psychobiological Responses Reveal Audiovisual Noise Differentially Challenges Speech Recognition.

Authors:  Gavin M Bidelman; Bonnie Brown; Kelsey Mankel; Caitlin Nelms Price
Journal:  Ear Hear       Date:  2020 Mar/Apr       Impact factor: 3.570

4.  Modelling Visual Search with the Selective Attention for Identification Model (VS-SAIM): A Novel Explanation for Visual Search Asymmetries.

Authors:  Dietmar Heinke; Andreas Backhaus
Journal:  Cognit Comput       Date:  2010-10-26       Impact factor: 5.418

5.  A comprehensive survey on techniques to handle face identity threats: challenges and opportunities.

Authors:  Mayank Kumar Rusia; Dushyant Kumar Singh
Journal:  Multimed Tools Appl       Date:  2022-06-10       Impact factor: 2.577

6.  Two-Dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component Analysis.

Authors:  Xiaoshuang Shi; Zhenhua Guo; Feiping Nie; Lin Yang; Jane You; Dacheng Tao
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2015-11-18       Impact factor: 6.226

7.  Dimensionality of object representations in monkey inferotemporal cortex.

Authors:  Sidney R Lehky; Roozbeh Kiani; Hossein Esteky; Keiji Tanaka
Journal:  Neural Comput       Date:  2014-07-24       Impact factor: 2.026

8.  Best basis selection method using learning weights for face recognition.

Authors:  Wonju Lee; Minkyu Cheon; Chang-Ho Hyun; Mignon Park
Journal:  Sensors (Basel)       Date:  2013-09-25       Impact factor: 3.576

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.