Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection

Understand

Multispectral pedestrian detection has received extensive attention in recent years as a promising solution to facilitate robust human target detection for around-the-clock applications (e.g.

• security surveillance and autonomous driving).
• In this paper, we demonstrate illumination information encoded in multispectral images can be utilized to significantly boost performance of pedestrian detection.
• A novel illumination-aware weighting mechanism is present to accurately depict illumination condition of a scene.