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Cutting-Edge Hand Gesture Recognition Speaker Technology

Explore innovative hand gesture recognition models for applications in remote input, touch-free car control, and selfie gestures. Utilize datasets like 20BN-jester and IBM DVS128 to develop advanced models. Learn from related works, including 3D Convolutional Neural Networks and Video Action Recognition. Stay updated on the latest advancements in this field.

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Cutting-Edge Hand Gesture Recognition Speaker Technology

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  1. Hand Gesture Recognition Speaker: 李奕承 Date:2019/2/15

  2. Outline • 1. Introduction • 2. Related work in model selection • 3. Collect data and do some experiment • 4. Our proposed model • 5. Reference

  3. 1.Introduction • 1. Remote input in Apple's notebook through TrueDepthcamera system • 2. Touch-free Car control • 3. Selfie hand gesture on the Sony Xperia XA Ultra

  4. 2.Related dataset • 1. The 20BN-jester Dataset V1 2. IBM DVS128 Gesture Dataset (CVPR 2017)

  5. 2.Related work in model selection • (a) Sequence to Sequence - Video to Text Jeff Donahue(2015 CVPR)

  6. 2.Related work in model selection • (b) Hand Gesture Recognition with 3D Convolutional Neural Networks PavloMolchanov, Shalini Gupta, Kihwan Kim, and Jan Kautz NVIDIA, Santa Clara, California, USA (2015 CVPR)

  7. 2.Related work in model selection • (b) Hand Gesture Recognition with 3D Convolutional Neural Networks PavloMolchanov, Shalini Gupta, Kihwan Kim, and Jan Kautz NVIDIA, Santa Clara, California, USA (2015 CVPR)

  8. 2.Related work in model selection • (c) Convolutional Two-Stream Network Fusion for Video Action Recognition Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman(2016 CVPR)

  9. 2.Related work in model selection • (c) Convolutional Two-Stream Network Fusion for Video Action Recognition What is Optical flow?

  10. 2.Related work in model selection • (d) Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset (CVPR 2017) https://arxiv.org/pdf/1705.07750.pdf

  11. Thank you !!

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