Multi-object tracking (MOT) holds a pivotal role in computer vision, but conventional prediction methods face limitations due to camera motion or missing detections. This paper introduces the Ego-motion Aware Target Prediction (EMAP) module to tackle these challenges.

• EMAP module integrates camera motion and depth information with object motion models to enhance tracking reliability.
• The method decouples camera motion impact from object trajectories, reducing disturbances and improving motion model performance.
• When combined with existing MOT algorithms, EMAP significantly drops identity switches and increases accuracy.

This innovation demonstrates a compelling improvement in the reliability of multi-object tracking, which is crucial for autonomous driving and surveillance systems. Read more.