Résumé
An event camera, also known as a neuromorphic camera, silicon retina or dynamic vision sensor, is an that responds to local changes in brightness. Event cameras do not capture images using a shutter as conventional (frame) cameras do. Instead, each pixel inside an event camera operates independently and asynchronously, reporting changes in brightness as they occur, and staying silent otherwise. Event camera pixels independently respond to changes in brightness as they occur. Each pixel stores a reference brightness level, and continuously compares it to the current brightness level. If the difference in brightness exceeds a threshold, that pixel resets its reference level and generates an event: a discrete packet that contains the pixel address and timestamp. Events may also contain the polarity (increase or decrease) of a brightness change, or an instantaneous measurement of the illumination level. Thus, event cameras output an asynchronous stream of events triggered by changes in scene illumination.Event cameras have microsecond temporal resolution, 120 dB dynamic range, and less under/overexposure and motion blur than frame cameras. This allows them to track object and camera movement (optical flow) more accurately. They yield grey-scale information. Initially (2014), resolution was limited to 100 pixels. A later entry reached 640x480 resolution in 2019. Because individual pixels fire independently, event cameras appear suitable for integration with asynchronous computing architectures such as neuromorphic computing. Pixel independence allows these cameras to cope with scenes with brightly and dimly lit regions without having to average across them. Indicates temporal resolution since human eyes and event cameras do not output frames. Temporal contrast sensors (such as DVS (Dynamic Vision Sensor) or sDVS (sensitive-DVS)) produce events that indicate polarity (increase or decrease in brightness), while temporal image sensors indicate the instantaneous intensity with each event.
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