Zhong , Lin2017-07-312017-07-312016-122016-08-02December 2Li Kam Wa, Robert. "Rethinking the Vision Sensing Pipeline for Energy Efficiency." (2016) Diss., Rice University. <a href="https://hdl.handle.net/1911/95563">https://hdl.handle.net/1911/95563</a>.https://hdl.handle.net/1911/95563The future of computing is in allowing our devices to see what we see: Continuous mobile vision. Wearable systems will continuously interpret vision data for real-time analytics for rich context-awareness. Unfortunately, today’s system software and imaging hardware are ill-suited for this goal of “continuous mobile vision.” Current systems -- highly optimized for photography -- fail to achieve sufficient energy efficiency for the minuscule energy capacity requirements of wearable batteries. This thesis provides a rethinking of the vision system stack that includes application frameworks, operating system and sensor hardware to improve efficiency by two orders of magnitude. This cross-layer rethinking contributes: (1) a split-process application framework that eliminates redundancy in data movement and processing across multiple concurrent applications, (2) operating system optimizations for energy proportional image capture, and (3) a mixed-signal image sensor architecture that processes data in the analog domain to eliminate the efficiency bottleneck of analog-digital conversion. By exploiting the hardware/software boundary for improved energy efficiency, this thesis opens the door to integrate our devices with our real-world environments and ultimately, our own lives.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.computer visionenergy efficiencymobile systemsmobile computingoperating systemscomputer architectureThesis2017-07-31