High-Performance Neuromorphic Sensor Processing

Neuromorphic, or event-based, sensors capture events at a microsecond resolution, which requires low-latency processing via FPGAs for real-time performance. By leveraging both the temporal and spatial components of the events, some algorithms, like a Hierarchy of event- based Time-Surfaces (HOTS), we find relationships between the two components for enhanced feature extraction and object detection. In contrast, using k-means clustering on spatial information can explore the tradeoff between increased accuracy at the expense of performance.