The Dynamic Vision Sensor (DVS) is an imaging sensor that processes the incident irradiance image and outputstemporal log irradiance changes in the image, such as those generated by moving target(s) and/or the moving sensorplatform. From a static platform, this enables the DVS to cancel out background clutter and greatly decrease the sensorbandwidth required to track temporal changes in a scene. However, the sensor bandwidth advantage is lost when imaginga scene from a moving platform due to platform motion causing optical flow in the background. Imaging from a movingplatform has been utilized in many recently reported applications of this sensor. However, this approach inherentlyoutputs background clutter generated from optical flow, and as such this approach has limited spatio-temporal resolutionand is of limited utility for target tracking applications. In this work we present a new approach to moving target trackingapplications with the DVS. Essentially, we propose modifying the incident image to cancel out optical flow due toplatform motion, thereby removing background clutter and recovering the bandwidth performance advantage of theDVS. We propose that such improved performance can be accomplished by integrating a hardware tracking andstabilization subsystem with the DVS. Representative simulation scenarios are used to quantify the performance of theproposed approach to clutter cancellation and improved sensor bandwidth.
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