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Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors
2019
Neuromorphic vision sensors are bio-inspired cameras that naturally capture the dynamics of a scene with ultra-low latency, filtering out redundant information with low power consumption. Few works are addressing the object detection with this sensor. In this work, we propose to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies. To make the best out of the event data, we introduce three different
doi:10.3929/ethz-b-000339165
fatcat:mbzxjbayazg2dko7korqoswziq