Occlusion handling and track management method of high-level sensor fusion for robust pedestrian tracking

In object tracking field, occlusion situations between objects are important factors that degrade the performance of tracking algorithms. In this paper, we present a track management method in the tracking level to solve the discontinuous tracking problem caused by occlusions between detected objects. This work is performed by predicting the occlusion situation between detected objects and managing the state of tracks based on an approach to track-to-track fusion in a high-level sensor fusion approach using a lidar and a monocular camera sensor. The occlusion prediction is computed by taking into account the width, length, position and azimuth angle of the detected objects. The track management system manages the occlusion state of the track from the result of occlusion prediction as well as the initialization, creation, confirmation and deletion of the tracks. The proposed approach has been verified in the occlusion situation between pedestrians, and our experimental results showed the intended performance in the occlusion situation between pedestrians.