Omnidirectional Video Capturing, Multiple People Tracking and Identification for Meeting Monitoring - Robotics Institute Carnegie Mellon University

Omnidirectional Video Capturing, Multiple People Tracking and Identification for Meeting Monitoring

Tech. Report, CMU-RI-TR-05-04, Robotics Institute, Carnegie Mellon University, 2005

Abstract

Meetings are a very important part of every day?s life for professionals working in universities, companies or governmental institutions. In fact, it is estimated that a mid-level manager or professional spends around 35% of his/her time in meetings. We have designed a physical awareness system called CAMEO (Camera Assisted Meeting Event Observer), a hardware/software component to record and monitor people's activities in meetings. CAMEO captures the audio and a high resolution omnidirectional view of the meeting by stitching images coming from almost concentric cameras. Besides recording capabilities, CAMEO automatically detects people and automatically learns a person-specific facial appearance model (PSFAM) for each of the participants. The PSFAMs allow more robust, reliable and faster tracking and identification. Several novelties in the video capturing device, multiple person identification and tracking are proposed. The effectiveness and robustness of the proposed system is demonstrated over several real time experiments and a large data set of videos.

BibTeX

@techreport{Frade-2005-9104,
author = {Fernando De la Torre Frade and Carlos Vallespi-Gonzalez and Paul Rybski and Manuela Veloso and Takeo Kanade},
title = {Omnidirectional Video Capturing, Multiple People Tracking and Identification for Meeting Monitoring},
year = {2005},
month = {January},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-05-04},
keywords = {omnidirectional vision, face recognition, discriminant analysis, adaptive face tracking.},
}