A multi-modal framework for continuous and isolated hand gesture recognition utilizing movement epenthesis detection
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00138-024-01565-9.pdf
Reference51 articles.
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2. Belgacem, S., Chatelain, C., Paquet, T.: Gesture sequence recognition with one shot learned crf/hmm hybrid model. Image Vis. Comput. 61, 12–21 (2017)
3. Benitez-Garcia, G., Olivares-Mercado, J., Sanchez-Perez, G., et al.: IPN Hand: a video dataset and benchmark for real-time continuous hand gesture recognition. In: 2020 25th International Conference on Pattern Recognition, pp. 4340–4347 (2021)
4. Camgoz, N.C., Hadfield, S., Koller, O., et al.: Using convolutional 3D neural networks for user-independent continuous gesture recognition. In: 2016 23rd International Conference on Pattern Recognition, pp. 49–54 (2016)
5. Camgoz, N.C., Hadfield, S., Bowden, R.: Particle filter based probabilistic forced alignment for continuous gesture recognition. In: 2017 IEEE International Conference on Computer Vision Workshops, pp. 3079–3085 (2017)
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