Venkatesh Kodukula
Robert LiKamWa
ABSTRACT
Energy-efficient visual sensing is extremely important to enable battery powered mobile and IoT applications. While several scheduling techniques have been proposed to save the digital power of sensing, the analog power [1] of capturing an image still remains a daunting barrier for a camera's energy-efficiency. To that end, we characterize the power and performance implications of analog voltage scaling on off-the-shelf image sensors. Our characterization reveals that while reducing the analog voltage supplied to image sensor helps promote sensor power efficiency, it also impairs imaging fidelity, specifically by making images brighter and noisier. Furthermore, we find that brighter and noisier images situationally affect the task accuracy of vision applications. In this poster, we propose an investigation towards a system that adaptively scales analog voltage to optimize sensor energy, while respecting the fidelity needs of visual tasks.
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Digital Library
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- Venkatesh Kodukula, Saad Katrawala, Britton Jones, Carole-Jean Wu, and Robert LiKamWa. Dynamic temperature management of near-sensor processing for energy-efficient high-fidelity imaging. Sensors, 2021.Google Scholar
Index Terms
- Adaptive voltage scaling to balance energy savings and image quality in cameras
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