A master-slave system to acquire biometric imagery of humans at distance

Xuhui Zhou, Robert T. Collins, Takeo Kanade, Peter Metes

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

121 Scopus citations

Abstract

The Distant Human Identification (DHID) system is a masterslave, real-time surveillance system designed to acquire biometric imagery of humans at distance. A stationary wide field of view master camera is used to monitor an environment at distance. When the master camera detects a moving person, a narrow field of view slave camera is commanded to turn to that direction, acquire the target human, and track them while recording zoomed-in images. These zoomed-in views provide meaningful biometric imagery of the distant humans, who are not recognizable in the master view. Based on the lenses we currently use, the system can detect and track moving people at distances up to 50 meters, within a 60° field of regard.

Original languageEnglish (US)
Title of host publication1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003
PublisherAssociation for Computing Machinery, Inc
Pages113-120
Number of pages8
ISBN (Electronic)158113780X, 9781581137804
DOIs
StatePublished - Nov 2 2003
Event1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003 - Berkeley, United States
Duration: Nov 2 2003Nov 8 2003

Publication series

Name1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003

Other

Other1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003
CountryUnited States
CityBerkeley
Period11/2/0311/8/03

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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    Zhou, X., Collins, R. T., Kanade, T., & Metes, P. (2003). A master-slave system to acquire biometric imagery of humans at distance. In 1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003 (pp. 113-120). (1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003). Association for Computing Machinery, Inc. https://doi.org/10.1145/982452.982467