Abstract
The recognition of human gestures and actions in images and videos is an active area of research in computer vision. This field has made great advances in the last decade thanks to the use of deep learning techniques. In addition, the recent diffusion of low-cost video camera systems, including depth cameras has enhanced the development of observation systems in a variety of application areas, such as video surveillance, home security, healthcare, etc. However, most of these developments are in closed and controlled environments. The recognition of movements and gestures in real-time through a camera that acquires its images in an uncontrolled environment (such as a shopping mall, a university lobby or a museum hall) and that allows interaction with passers-by in these spaces, contains challenges in various areas that include at least technological, social and legal challenges that need a careful approach. Within this framework, we set as objectives of this project the design of a web interface adapted to interaction without physical contact (i.e., through video images captured with a camera in real-time) and the construction of artificial intelligence models (based on deep learning) that guarantee, in an uncontrolled environment, an interaction with this web interface. As a first step in this work, we propose a literature review in this area. In addition, we include model recognition for a given set of gestures to explore the possibilities of different approaches.
This work was partially supported by Doctorado industrial, Comunidad Autónoma de La Rioja, and Grant PID2020-115225RB-I00 funded by MCIN/AEI/ 10.13039/501100011033.
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Alvear, V., Domínguez, C., Mata, G. (2023). Human Action Recognition in Uncontrolled Environments: Application from Artificial Intelligence to Contactless Interfaces. In: Novais, P., et al. Ambient Intelligence – Software and Applications – 14th International Symposium on Ambient Intelligence. ISAmI 2023. Lecture Notes in Networks and Systems, vol 770. Springer, Cham. https://doi.org/10.1007/978-3-031-43461-7_26
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