Affiliations: [a] Faculty of Applied Engineering, University of Antwerp, 2020 Antwerp, Belgium | [b] Deparment of Mathematics, University of Antwerp, 2020 Antwerp, Belgium
Correspondence:
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Corresponding author: Steve Vanlanduit, Faculty of Applied Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium. E-mail: [email protected].
Abstract: A robust method is proposed for people tracking using range cameras: Density Map Tracking with Blob Splitting (DMT-BS). It was designed primarily for worker safety in industrial environments, but can be used in other applications as well. Multiple cameras can easily be added to resolve occlusions and to enlarge the observed area. The method could be used to track any moving object in an otherwise static environment as the detection does not rely on a specific human model. Its strength lies in its simplicity, making the behavior predictable and opening possibilities to be implemented on low-cost hardware. From the point cloud delivered by the depth sensor, a 2D density map is formed in floor coordinates followed by basic 2D-tracking. Robustness of this tracking is enhanced using a simple but effective blob splitting technique. Tests show that the camera position, depth noise, and extrinsic calibration errors have little influence on the tracker’s performance. The proposed method was tested on three depth tracking datasets, reaching significantly better MOTA (Multiple Object Tracking Accuracy) scores when compared to two state-of-the-art depth-based trackers.
Keywords: Human tracking, depth camera, time-of-flight, RGB-D, industrial safety
