Fast Foveating Cameras for Dense Adaptive Resolution
IEEE Transactions on Pattern Analysis and Machine Intelligence(2022)
摘要
Traditional cameras field of view (FOV) and resolution predetermine computer vision algorithm performance. These trade-offs decide the range and performance in computer vision algorithms. We present a novel foveating camera whose viewpoint is dynamically modulated by a programmable micro-electromechanical (MEMS) mirror, resulting in a natively high-angular resolution wide-FOV camera capable of densely and simultaneously imaging multiple regions of interest in a scene. We present calibrations, novel MEMS control algorithms, a real-time prototype, and comparisons in remote eye-tracking performance against a traditional smartphone, where high-angular resolution and wide-FOV are necessary, but traditionally unavailable.
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