Volume XLII-2/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 179-183, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 179-183, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-179-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 May 2019

09 May 2019

AUTOMATIC DETECTION AND RECOGNITION OF 3D MANUAL GESTURES FOR HUMAN-MACHINE INTERACTION

D. Ryumin, I. Kagirov, D. Ivanko, A. Axyonov, and A. A. Karpov D. Ryumin et al.
  • St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, SPIIRAS, Saint-Petersburg, Russian Federation

Keywords: Sign Language, Gestures, Face Detection, Computer Vision, Machine Learning, Neural Networks

Abstract. In this paper, we propose an approach to detect and recognize 3D one-handed gestures for human-machine interaction. The logical structure of the modules of the system for recording a gestural database is described. The logical structure of the database of 3D gestures is presented. Examples of frames showing gestures in the format of Full High Definition, in the map depth mode and in the infrared illustrated. Models of a deep convolutional network for detecting faces and hand shapes are described. The results of automatic detection of the area with the face and the shape of the hand are given. Identified the distinctive features of the gesture at a certain point in time. The process of recognizing 3D one-handed gestures is described. Due to its versatility, this method can be used in tasks of biometrics, computer vision, machine learning, automatic systems of face recognition, sign languages.