Utilization of Occluded Detections and Target Information in Multi-Person Tracking
Abstract
Multi-person tracking has many applications such as surveillance or automated driving. Existing approaches exploit available motion and appearance cues insufficiently. In contrast, this work introduces several methods to improve the usage of detections and target information, including novel association strategies, distance measures, and an occlusion-aware initialization. The proposed framework achieves state-of-the-art results on multiple benchmarks and tracks hundreds of persons in real time.
Fields of Study & Subjects
Video Surveillance and Tracking Methods
Autonomous Vehicle Technology and Safety
Target Tracking and Data Fusion in Sensor Networks
Publication details
- Journal / source
- Repository KITopen (Karlsruhe Institute of Technology)
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Thesis