Abstract
High-speed CMOS video sensors play an increasingly important role in capturing rapid motion for manufacturing, research, and entertainment purposes. Though highly refined commercial systems have become more readily available, they remain costly due to the intensive data storage and throughput requirements of high speed capture. Moreover, there are upper limits on capture rates due to hardware limitations regardless of cost. Recent developments in compressive imaging have opened up new avenues for bypassing some of these challenges by encoding motion optical at capture time. We explore strategies for encoding motion in a single capture by translating a binary physical mask during the exposure. By comparing, in simulation, a variety of mask patterns and reconstruction algorithms, we determine a strategy that provides high quality results relative to ground truth as well as computationally efficient reconstruction. We demonstrate this strategy in a custom-built hardware prototype.