Fusing 8x8 ToF and IR sensors with a 6343-parameter CNN achieves 92.3% accuracy and 0.93 macro F1 on 7 static gestures while running at millisecond latency and 50 mW on STM32 MCUs.
://arxiv.org/abs/2412.01508, https://arxiv.org/abs/2412.01508 arXiv:2412.01508
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A literature review that categorizes deep learning approaches for visual hand gesture recognition, summarizes state-of-the-art methods across tasks, reviews datasets and metrics, and identifies challenges and future directions.
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Efficient Sensor Fusion for Gesture Recognition on Resource-Constrained Devices
Fusing 8x8 ToF and IR sensors with a 6343-parameter CNN achieves 92.3% accuracy and 0.93 macro F1 on 7 static gestures while running at millisecond latency and 50 mW on STM32 MCUs.
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Visual Hand Gesture Recognition with Deep Learning: A Comprehensive Review of Methods, Datasets, Challenges and Future Research Directions
A literature review that categorizes deep learning approaches for visual hand gesture recognition, summarizes state-of-the-art methods across tasks, reviews datasets and metrics, and identifies challenges and future directions.