Keeping Track of Humans: Have I Seen This Person Before?
- 18 January 2006
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2081-2086
- https://doi.org/10.1109/robot.2005.1570420
Abstract
In this paper we describe a system that enables a mobile robot equipped with a color vision system to track humans in indoor environments. We developed a method for tracking humans when they are within the field of view of the camera, based on motion and color cues. However, the robot also has to keep track of humans which leave the field of view and re-enter later. We developed a dynamic Bayesian network for such a global tracking task. Experimental results on real data confirm the viability of the developed method. Index Terms— Human-robot interaction, people tracking, vision-based user interfaces.Keywords
This publication has 16 references indexed in Scilit:
- Detecting moving shadows: algorithms and evaluationIeee Transactions On Pattern Analysis and Machine Intelligence, 2003
- Multi-modal anchoring for human–robot interactionRobotics and Autonomous Systems, 2003
- People Tracking with Mobile Robots Using Sample-Based Joint Probabilistic Data Association FiltersThe International Journal of Robotics Research, 2003
- MINERVA: a second-generation museum tour-guide robotPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Adaptive background mixture models for real-time trackingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Illumination-invariant color object recognition via compressed chromaticity histograms of color-channel-normalized imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Real-time tracking of non-rigid objects using mean shiftPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Object identification: a Bayesian analysis with application to traffic surveillanceArtificial Intelligence, 1998
- The estimation of the gradient of a density function, with applications in pattern recognitionIEEE Transactions on Information Theory, 1975
- Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric ProblemsThe Annals of Statistics, 1974