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Abstract

Computer vision has been applied widely in cybersecurity, specially for authentication purposes like iris or fingerprint recognition. Image processing techniques also allow to understand hand gestures of the sign language alphabet, among others. Combining both approaches, in this paper, a system to detect the hand SOS gesture is proposed. By training a model to understand hand gestures, the detection of a certain sequence of hand gestures make possible to identify the SOS signal. The proposed method can be deployed in surveillance systems and others devices with a camera such as social robots. So, victims can ask for help silently and alarms can inform the authorities automatically.

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Acknowledgement

Virginia Riego would like to thank Universidad de León for its funding support for her doctoral studies.

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Correspondence to Lidia Sánchez-González .

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Viejo-López, R., Riego del Castillo, V., Sánchez-González, L. (2023). Hand SOS Gesture Detection by Computer Vision. In: García Bringas, P., et al. International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022). CISIS ICEUTE 2022 2022. Lecture Notes in Networks and Systems, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-031-18409-3_3

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