Frame-free dynamic digital vision

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CIFAR10-DVS: An Event-Stream Dataset for Object Classification (2017, background): “Neuromorphic vision based on neuromorphic cameras (Delbruck, 2008; Lichtsteiner et al., 2008; Serrano-Gotarredona and Linares-Barranco, 2013; Yang et al., 2015) which converts visual information to address-event-representation (AER; Boahen, 2000) event streams has garnered increasing attention.”
CAVIAR: A 45k Neuron, 5M Synapse, 12G Connects/s AER Hardware Sensory–Processing– Learning–Actuating System for High-Speed Visual Object Recognition and Tracking (2009, background): “It captures and time-stamps events to a computer at peak rates of up to 100 kilo events per second (keps) and is particularly useful for portable demonstrations, and the components cost is less than $20 [22].”
Neuromorphic sensory systems. (2010, background): “For example, local features like orientation and motion can be extracted using temporal coherence and relative timing of events [56].”
Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator (2014, background): “Computational vision typically presents a static image in a completed frame, but significant speedups can be achieved if visual information is processed in a frame-free manner [1], [2],”
Event-Based Vision: A Survey (2019, background): “A TS is a 2D map where each pixel stores a single time value (e.g., the timestamp of the last event at that pixel [92], [93]).”