People in videos from people in pictures

Jehanzeb Abbas, Charlie K. Dagli, Thomas S. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose an appearance based model for face recognition in news videos using an enormously large databank of still images. This is a step towards building an elaborate face-query system using multimodal audio-visual data. We use the fact that faces of the same person appear similar than of different people. We preprocess the videos, apply feature extraction, feature matching and a unique parallel line matching algorithm to develop a simple yet a powerful face recognition system. We tested our approach on real world data and the results show good performance both for high resolution still images and low resolution news videos without involving any training or tasks like face rectification, warping etc. It can be incorporated as part of a larger multimodal news video analysis system with problems of time alignment between text and faces. Our results show that this simple approach also works well where video modality is the only source of information.

Original languageEnglish (US)
Title of host publicationMIPPR 2007
Subtitle of host publicationPattern Recognition and Computer Vision
DOIs
StatePublished - Dec 1 2007
EventMIPPR 2007: Pattern Recognition and Computer Vision - Wuhan, China
Duration: Nov 15 2007Nov 17 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6788
ISSN (Print)0277-786X

Other

OtherMIPPR 2007: Pattern Recognition and Computer Vision
Country/TerritoryChina
CityWuhan
Period11/15/0711/17/07

Keywords

  • Face recognition
  • Multi-modal video analysis
  • Video mining

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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