Exploiting Temporal Coherence to Improve Person Re-identification

Abstract

The uncontrolled characteristics of long-term scenarios, like ultra-running competitions, are challenging for person re-identification approaches based on computer vision methods. State-of-the-art techniques have reported hardly moderate success for whole-body runner re-identification due to the existence of distinct illumination conditions, as well as changes of clothing and/or accessories like backpacks, caps, and sunglasses. This paper explores integrating these biometric cues with the particular spatio-temporal context information present in the competition live track system. Our results confirm the significance of this strategy to limit the gallery size and boost re-identification performance.