Real Time Recognition of Sign Language Using Convolutional Neural Network

References

[1] H. Muthu Mariappan and V. Gomathi, “Real-Time Recognition of Indian Sign Language,” 2019 International Conference on Computational Intelligence in Data Science (ICCIDS), Chennai, India, 2019, pp. 1- 6, doi: 10.1109/ICCIDS.2019.8862125.

[2] Rokade, Yogeshwar & Jadav, Prashant. (2017), “Indian Sign Language Recognition System,” International Journal of Engineering and Technology. 9. 189-196. 10.21817/ijet/2017/v9i3/170903S030.

[3] Saurabh Kumbhar, Abhishek Landge, Akash Kulkarni, Devesh Solanki, Vidya Kurtadikar, “Indian Sign Language Recognition System,” June – 2021 International Journal of Innovative Science and Research Technology Volume 6, Issue 6.

[4] Khan A, Sohail A, Zahoora U, Qureshi AS,”A survey of the recent architectures of deep convolutional neural networks,” Artif Intell Rev. 2020;53(8):5455–516.

[5] J. Redmon, S. Divvala, R. Girshick and A. Farhadi, "You Only Look Once: Unified, Real-Time Object Detection," 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 779-788, doi: 10.1109/CVPR.2016.91.

[6] Wang, C.-Y., Bochkovskiy, A. & Liao, H.-Y.M,” YOLOv7: Trainable bag-of-freebies sets new state-of- the-art for real-time object detectors,”. Available at: https://arxiv.org/abs/2207.02696v1.

[7] Jacob Solawetz, Joseph Nelson, PP-YOLO Surpasses “YOLOv4 - State of the Art Object Detection Techniques”

[8] Saxena, Rohan and Garg, Romy and Gupta, Bhoomi and Kaur, Narinder, “Hand Gesture Recognition” (February 4, 2022). Available at SSRN.

[9] Raheja, J.L., Mishra, A. & Chaudhary, A. “Indian sign language recognition using SVM.” Pattern Recognit. Image Anal. 26, 434–441 (2016).

[10] Singha, Joyeeta, and Karen Das, "Indian sign language recognition using eigen value weighted Euclidean distance-based classification technique," arXiv preprint arXiv:1303.0634 (2013).

[11] D. Deora and N. Bajaj, "Indian sign language recognition," 2012 1st International Conference on Emerging Technology Trends in Electronics, Communication & Networking, 2012, pp. 1-5.

[12] Bhavadharshini M, Josephine Racheal J, Kamali M, Sankar S, Volume 40: “Advances in Parallel Computing Technologies and Applications”, pp. 159–166.

[13] V. Adithya, R. Rajesh, Hand gestures for emergency situations, “A video dataset based on words from Indian sign language”, Data in Brief, Volume 31, 2020, 106016, ISSN 2352-3409.

[14] Anup Nandy, Jay Shankar Prasad, Soumik Mondal, Pavan Chakraborty, G. C. Nandi, “Recognition of Isolated Indian Sign Language Gesture in Real Time,” Information Processing and Management, 2010, Volume 70.

[15] Bui, Hien Minh, “Hand Sign Language RecognitionWith Artificial Intelligence” Using “You Only Look Once” (Yolo) model as a case 2022 Bachelor Thesis Degree Programme in Business Information Technology Bachelor of Business Administration.

[16] Saxena, R., Garg, R., Gupta, B., Kaur, N. (2023). Deep Learning Based Hand Sign Recognition in the Context of Indian Greetings and Gestures. In: Joby, P.P., Balas, V.E., Palanisamy, R. (eds) IoT Based Control Networks and Intelligent Systems. Lecture Notes in Networks and Systems, vol 528. Springer, Singapore.

[17] Kashish Shah, Sanket Rathi, Rishabh Shetty, Kamal Mistry, “A Comprehensive Review on Text to Indian Sign Language Translation Systems, Smart Trends in Computing and Communications”, 2022, Volume 286.

[18] Ashok Kumar Sahoo, Pradeepta Kumar Sarangi, Chandra Shekhar Yadav, Indian Sign Language Recognition Using Ensemble Based Classifier Combination Macromelecular Synmposia, 10.1002/masy.202100286, 401, 1, (2022).

[19] J. -H. Sun, T. -T. Ji, S. -B. Zhang, J. -K. Yang and G. -R. Ji, "Research on the Hand Gesture Recognition Based on Deep Learning," 2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE), 2018, pp. 1-4, doi: 10.1109/ISAPE.2018.8634348.

[20] D. Tasmere, B. Ahmed and M. M. Hasan, "Bangla Sign Digits: A Dataset For Real Time Hand Gesture Recognition," 2020 11th International Conference on Electrical and Computer Engineering (ICECE), 2020, pp. 186-189, doi: 10.1109/ICECE51571.2020.9393070.

[21] M. A. Rahim, J. Shin and M. R. Islam, "Dynamic Hand Gesture Based Sign Word Recognition Using Convolutional Neural Network with Feature Fusion," 2019 IEEE 2nd International Conference on Knowledge Innovation and Invention (ICKII), 2019, pp. 221-224, doi: 10.1109/ICKII46306.2019.9042600.

[22] C. Liu, Y. Tao, J. Liang, K. Li and Y. Chen, "Object Detection Based on YOLO Network," 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), 2018, pp. 799-803, doi: 10.1109/ITOEC.2018.8740604.

[23] A. M. Algorry, A. G. García and A. G. Wofmann, "Real- Time Object Detection and Classification of Small and Similar Figures in Image Processing," 2017 International Conference on Computational Science and Computational Intelligence (CSCI), 2017, pp. 516-519, doi:10.1109/CSCI.2017.8.

@article{1704136,
      author = {Sejal Vasan, Tushar Bhutani, Amita Goel, Nidhi Sengar, Vasudha Bahl},
      title = {Real Time Recognition of Sign Language Using Convolutional Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {9},
      pages = {29-36},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704136.pdf},
      abstract = {Around 1 million to 2.7 million Indians use Indian Sign Language to communicate; this figure clearly states how important it is to augment a strong and dependable system for easy communication. Sign language is mostly learned by the deaf and dumb and is most likely unknown to others; as a result, communication becomes difficult. With the advancement of time, various approaches have emerged for smooth communication using sign language. The most common technique for interpretation involves using image processing algorithms to draw out features from coordinated motions, then applying convolutional neural networks (CNN) to master these characteristics and improve their functionality. An algorithm that can identify and predict objects in one forward pass is You Only Look Once (YOLO). In this study specifically Yolov7 i.e., the latest model of the Yolo series was used. The development of a system that enables individuals to utilise sign language independently can significantly aid them in being independent and ignite the confidence to exhibit their individuality to the public fearlessly. Therefore, it is crucial to create a hand gesture recognition system that can recognise hand signs in a developing nation like India with utmost accuracy. Our study dealt with developing a static hand gesture recognition algorithm to detect Indian Sign Language gestures used to communicate in our day-to-day lives. The machine learning model built was able to provide a perfect precision-recall graph, with 99% precision and recall.},
      keywords = {Indian Sign Language, Convolutional Neural Networks, You Only Look Once},
      month = {March},
  }