Human-like sign-language learning method using deep learning |
Ji, Yangho
(Department of Electrical Engineering, Kwangwoon University)
Kim, Sunmok (Department of Electrical Engineering, Kwangwoon University) Kim, Young-Joo (Logistics System Research Team, Korea Railroad Research Institute) Lee, Ki-Baek (Department of Electrical Engineering, Kwangwoon University) |
1 | J. Singha et al., Recognition of Indian sign language in live video, arXiv: 1306-1301, 2013. |
2 | B. Garcia et al., Real-time American sign language recognition with convolutional neural networks, Convolutional Neural Netw. for Vis. Recogn. (2016), 225-232. |
3 | O. Kang, Sign language (The most valuable language in the world) , Light and Fragrance, 2001. |
4 | J.-Y. Lee et al., A real-time hand gesture recognition technique and its application to music display system, J. Autom. Contr. Eng. 4 (2016), no. 2, 177-180. DOI |
5 | D. Weinland et al., Free viewpoint action recognition using motion history volumes, Comput. Vis. Image Underst. 104, (2006) 249-257. DOI |
6 | O. Russakovsky et al., Imagenet large scale visual recognition challenge, Int. J. of Comput. Vis. 115 (2015), 211-252. DOI |
7 | K. Simonyan et al., Very deep convolutional networks for largescale image recognition, arXiv preprint arXiv: 1409.1556, 2014. |
8 | D. Kingma et al., A method for stochastic optimization, arXiv preprint arXiv: 1412.6980, 2014. |
9 | S. Ioffe et al., Batch normalization: Accelerating deep network training by reducing internal covariate shift, arXiv preprint arXiv: 1502.03167, 2015. |
10 | K. He et al., Deep residual learning for image recognition, Proc. IEEE Conf. Comput. Vis. Pattern Recogn., Las Vegas, NV, USA, June 27-30, 2016, pp. 770-778. |
11 | A. Agarwal et al., Sign language recognition using Microsoft Kinect, IEEE Int. Conf. Contemp. Comput., Noida, India, Aug. 8-10, 2013, pp. 181-185. |
12 | O. Koller et al., Deep learning of mouth shapes for sign language, Proc. IEEE Int. Conf. Comput. Vis. Workshops, Santiago. Chile, Dec. 7-13, 2015, pp. 477-483. |
13 | D. Wu et al., Deep dynamic neural networks for multimodal gesture segmentation and recognition, IEEE Trans. Pattern Anal. Mach. Intell. 38 (2016), no. 8, 1583-1597. DOI |
14 | J. Huang et al., Sign language recognition using 3d convolutional neural networks, IEEE Int. Conf. Multimed. Expo, Turin, Italy, June29-July 3, 2015, pp. 1-6. |
15 | D. Wu et al., Deep dynamic neural networks for gesture segmentation and recognition, Workshop Eur. Conf. Comput. Vis. 38 (2014), no. 8, 1583-1597. |
16 | C. Xiujuan et al., Sign language recognition and translation with Kinect, IEEE Int. Conf. on AFGR 655 (2013). |
17 | I. Lim et al., Sign-language recognition through gesture & movement analysis (SIGMA), DLSU Res. Congress 2, Manila, Philippine, Mar. 2-4, 2015, p. HCT-I-011. |
18 | L. Pigou et al., Sign language recognition using convolutional neural networks, Workshop Eur. Conf. Comput. Vis., Zurich, Swiss, Sept. 6-12, 2014, pp. 572-578. |
19 | H. Cooper et al., Sign language recognition using sub-units, J. Mach. Learn. Res. 13 (2017), no. 1, 2205-2231. |
20 | H. Liu et al., Gesture recognition for human-robot collaboration: A review, Int. J. of Ind. Ergon. 2017. |
21 | O. Koller et al., Deep Sign: Hybrid CNN-HMM for continuous sign language recognition, Proc. Br. Mach. Vis. Conf., York, UK, Sept. 19-22, 2016. |
22 | Y. L. Gweth et al., Enhanced continuous sign language recognition using PCA and neural network features, IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn. Workshops, Providence, RI, USA, June 16-21, 2012, pp. 55-60. |
23 | N. Neverova et al., Multi-scale deep learning for gesture detection and localization, Workshop Eur. Conf. Comput. Vis., Zurich, Swiss, Sept. 6-12, 2014, pp. 1-17. |
24 | O. Koller et al., Continuous sign language recognition: Towards large vocabulary statistical recognition systems handling multiple signers, Comput. Vis. Image Underst. 141 (2015), 108-125. DOI |
25 | M. Oliveira et al., A comparison between end-to-end approaches and feature extraction based approaches for sign language recognition, Int. Conf. on Image and Vis. Comput. New Zealand, Christchurch, New Zealand, Dec. 4-6, 2017, pp. 1-5. |
26 | J. Forster et al., Improving continuous: Speech recognition techniques and system design, Workshop Speech Lang. Process. Assist. Technol., Grenoble, France, Aug. 21-22, 2013, pp. 41-46. |
27 | S. Jain et al., Indian sign language gesture recognition, 2015. |
28 | A. K. Sahoo et al., Sign language recognition: state of the art, ARPN J. Eng. Applicat. Sci. 9 (2014), 116-134. |