Face tracking using Kalman filter with dynamic noise statistics

Pavan Turaga, Gurprakash Singh, P. K. Bora

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

2 Scopus citations

Abstract

We present a system for automatic detection and tracking of faces in video sequences. Detection is done based on a statistical characterization of skin-color. The position and size of the dominant face are estimated using statistical means of the binary map projections. Tracking is done using a Kalman filter. We propose a novel technique for updating the process noise covariance at each iteration. The algorithm performs well on a variety of real-life videos. The algorithm is (1) able to automatically detect the initial position and size of face, (2) relatively insensitive to lighting condition variations, (3) robust against partial occlusions (4) able to track in case of scale changes. Experimental results demonstrate the effectiveness of the algorithm on a variety of videos.

Original languageEnglish (US)
Title of host publicationIEEE Region 10 Annual International Conference, Proceedings/TENCON
VolumeA
StatePublished - 2004
Externally publishedYes
EventIEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering - Chiang Mai, Thailand
Duration: Nov 21 2004Nov 24 2004

Other

OtherIEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering
Country/TerritoryThailand
CityChiang Mai
Period11/21/0411/24/04

ASJC Scopus subject areas

  • Engineering(all)

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