Underlying the advantages of neuromorphic vision systems is an approach called event-based vision. Event-based vision is driving a paradigm shift away from an image capture method that has been used for more than a century: frame-based capture.
Such an approach delivers substantial advantages, including:
- Speed — Enabled by microsecond timestamping and reduced time to action
- Data efficiency — Filtering out redundant, static data at the pixel level, before it hits the CPU
- Light sensitivity — High dynamic range and low light sensitivity
- Energy efficiency: Less power consumption for always-on, mobile and remote use cases
Many applications require high image quality not possible with event-based cameras alone. Hybrid frame/event-based approaches can utilize the best characteristics of each. With a hybridapproach, event-based vision can be used to acquire fewer frames and use asynchronous events to fill the gaps between them, which in turn reduces bandwidth and ultimately power consumption.
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