ISPRS-Archives ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLII-2-W12-179-2019 AUTOMATIC DETECTION AND RECOGNITION OF 3D MANUAL GESTURES FOR HUMAN-MACHINE INTERACTION Ryumin D. 1 Kagirov I. 1 Ivanko D. 1 Axyonov A. 1 Karpov A. A. 1 St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, SPIIRAS, Saint-Petersburg, Russian Federation 09 05 2019 XLII-2/W12 179 183 Copyright: © 2019 D. Ryumin et al. 2019 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-2-W12-179-2019.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-2-W12-179-2019.pdf

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.