Carnegie Mellon University
Appearance-Based Face Recognition and Light-Fields

Ralph Gross, Iain Matthews, and Simon Baker
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 4, pp. 449 - 465, May, 2004.

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Arguably the most important decision to be made when developing an object recognition algorithm is selecting the scene measurements or features on which to base the algorithm. In appearance-based object recognition the features are chosen to be the pixel intensity values in an image of the object. These pixel intensities correspond directly to the radiance of light emitted from the object along certain rays in space. The set of all such radiance values over all possible rays is known as the plenoptic function or light-field. In this paper we develop a theory of appearance-based object recognition from light-fields. This theory leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards. All of the pixels, whichever image they come from, are treated equally and used to estimate the (eigen) light-field of the object. The eigen light-field is then used as the set of features on which to base recognition, analogously to how the pixel intensities are used in appearance-based face and object recognition.

Appearance-based object recognition, face

Sponsor: US Office of Naval Research
Grant ID: N00014-00-1-0915
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Human Identification at a Distance, Face Group, Component Analysis
Associated Project(s): Light-fields, Face Recognition Across Pose, Face Recognition
Number of pages: 37

Text Reference
Ralph Gross, Iain Matthews, and Simon Baker, "Appearance-Based Face Recognition and Light-Fields," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 4, pp. 449 - 465, May, 2004.

BibTeX Reference
   author = "Ralph Gross and Iain Matthews and Simon Baker",
   title = "Appearance-Based Face Recognition and Light-Fields",
   journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
   pages = "449 - 465",
   month = "May",
   year = "2004",
   volume = "26",
   number = "4",