| Paper: | TA-P1.9 |
| Session: | Video Surveillance I / Document Image Processing & Analysis |
| Time: | Tuesday, September 18, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
TRACKING PERSONS USING PARTICLE FILTER FUSING VISUAL AND WI-FI LOCALIZATIONS FOR WIDELY DISTRIBUTED CAMERA |
| Authors: |
Takashi Miyaki; University of Tokyo | | |
| | Toshihiko Yamasaki; University of Tokyo | | |
| | Kiyoharu Aizawa; University of Tokyo | | |
| Abstract: |
This paper describes an object tracking scheme employs sensor fusion approach which is composed of visual information and location information estimated from Wi-Fi signals. Location information is calculated by a set of received signal strength values of beacon packets from Wi-Fi access points (APs) around the targets. Different from the conventional approaches which use another kind of sensors, our approach can cover wider areas both indoor and outdoor with lower cost because of characteristics of Wi-Fi signals. Particle filter is applied to combine these two different kinds of sensory input to track the target continuously. Wi-Fi observation model is involved in a conventional visual particle filtering scheme in order to evaluate importance weights of each particle. By using multiple modality, robust tracking performance is achieved even if reliability of one sensory input declines. In this paper, we present experimental results applied to outdoor surveillance camera environment. |
