RGB-D and Thermal Sensor Fusion: Application in Person Tracking

摘要

Many systems combine RGB cameras with other sensor modalities for fusing visual data with complementary environmental information in order to achieve improved sensing capabilities. This article explores the possibility of fusing a commodity RGB-D camera and a thermal sensor. We show that using traditional methods, it is possible to accurately calibrate the complete system and register the three RGB-D-T data sources. We propose a simple person tracking algorithm based on particle filters, and show how to combine the mapped pixel information from the RGB-D-T data. Furthermore, we use depth information to adaptively scale the tracked target area when radial displacements from the camera occur. Experimental results provide evidence that this allows for a significant tracking performance improvement in situations with large radial displacements, when compared to using only a tracker based on RGB or RGB-T data.