Neuromorphic Vision-Based Fall Localization in Event Streams With Temporal–Spatial Attention Weighted Network

Abstract

Falling down is a serious problem for health and has become one of the major etiologies of accidental death for the elderly living alone. In recent years, many efforts have been paid to fall recognition based on wearable sensors or standard vision sensors. However, the prior methods have the risk of privacy leaks, and almost all these methods are based on video clips, which cannot localize where the falls occurred in long videos. For these reasons, in this article, the bioinspired vision sensor-based falls temporal localization framew Show more