6533b7dafe1ef96bd126e246
RESEARCH PRODUCT
An adaptive multi-rate system for visual tracking in augmented reality applications
M. MassaroAntonino SferlazzaFilippo D'ippolitosubject
0209 industrial biotechnologyEngineering02 engineering and technologyAugmented reality01 natural sciences010305 fluids & plasmas020901 industrial engineering & automationSettore ING-INF/04 - Automatica0103 physical sciencesParameter estimationComputer visionMulti-rateVisual trackingbusiness.industryTracking systemKalman filterData fusionObject (computer science)Object detectionMulti-sensorVideo trackingTrajectoryEye trackingAugmented realityArtificial intelligencebusinessMEMS inertial sensordescription
The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracking of an object in augmented reality environments. The multi-sensor system consists of a webcam and a 3-axis MEMS inertial sensor both with different sample rates. The augmented reality application has been designed for the object detection problem, and it has been tested experimentally in a suitably developed test set-up.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-06-01 |