Hand Gesture Recognition Using Deep Neural Network and Its Implementation in Augmented Reality
Huayong Yang, Xiaoli Lin
Available Online January 2017.
- 10.2991/icmmita-16.2016.203How to use a DOI?
- landmark detection; gesture recognition; object recognition; augmented reality.
In this paper, we study the augmented reality and its application in intelligent human-computer interaction. The complex structure in the visual background is a major challenge for gesture segmentation. First, we use a robust skin color segmentation method to preprocess the input image. Second, visual texture features are analyzed and modeled for hand region recognition. Third, finger landmarks are annotated and configured by active shape model. Finally, the hand gestures are recognized and used for enhanced interaction. Experimental results show that the proposed gesture recognition system is robust against various background changes and illumination changes.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Huayong Yang AU - Xiaoli Lin PY - 2017/01 DA - 2017/01 TI - Hand Gesture Recognition Using Deep Neural Network and Its Implementation in Augmented Reality BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.203 DO - 10.2991/icmmita-16.2016.203 ID - Yang2017/01 ER -