Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach Interuniversity Microelectronics Centre Ghent University KU Leuven
Drones are currently being explored for safety-critical applications where human agents are expected to evolve in their vicinity. In such applications, robust people avoidance must be provided by fusing a number of sensing modalities in order to avoid collisions. Currently however, people detection systems used on drones are solely based on standard cameras besides an emerging number of works discussing the fusion of imaging and event-based ...