Abstract
We present a multi-camera system based on Bayesian modality fusion to track multiple people in an indoor environment A Bayesian network is used to combine multiple modalities for matching subjects between multiple camera views. Unlike other occlusion reasoning methods, we use multiple cameras to obtain continuous visual information of people in either or both cameras so that they can be tracked through interactions. Results demonstrate that the system can maintain people’s identities by using multiple cameras cooperatively.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
