Injoon Hong, Dongjoo Shin, Youchang Kim, Kyeongryeol Bong, Seongwook Park, K. Lee, H. Yoo
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引用次数: 1
Abstract
In this paper, a low-power real-time gaze-activated object recognition processor is proposed for a battery-powered smart glasses system. For high energy efficiency, we propose keypoint-level pipelined architecture to increase the hardware utilziation which results in significant power reduction of the real-time recognition processor. In addition, low-power gaze-activation image sensor with mixed-mode architecture is proposed for the glass user's gaze estimation. Therefore, only the small image region where the glasses user is seeing needs to be processed by the recognition processor leading to further power reduction. As a result, the proposed object recognition processor shows 30fps real-time performance only with 75mW power consumption, which is 3.5x and 4.4x smaller power than the state-of-the-art works.
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