Novel Hand Gesture Alert System

Abstract

. Sexual assault can cause great societal damage, with negative socio-economic, mental, sexual, physical and reproductive consequences. According to the Eurostat, the number of crimes increased in the European Union between 2008 and 2016. However, despite the increase in security tools such as cameras, it is usually difficult to know if an individual is subject to an assault based on his or her posture. Hand gestures are seen by many as the natural means of nonverbal communication when interacting with a computer, and a considerable amount of research has been performed. In addition, the identifiable hand placement characteristics provided by modern inexpensive commercial depth cameras can be used in a variety of gesture recognition-based systems, particularly for human-machine interactions. This paper introduces a novel gesture alert system that uses a combination of Convolution Neural Networks (CNNs). The overall system can be subdivided into three main parts: firstly, the human detection in the image using a pretrained “You Only Look Once (YOLO)” method, which extracts the related bounding boxes containing his/her hands; secondly, the gesture detection/classification stage, which processes the bounding box images; and thirdly, we introduced a module called “counterGesture”, which triggers the alert.

Helping Hearing-Impaired in Emergency Situations: A Deep Learning-Based Approach

“…They implemented both static and dynamic gestures recorded on a video and attained an accuracy of 97.68%. Mambou et al [46] suggested a sexual assault alert system from various scenes at night. The model was implemented on a combination of YOLO and CNN architecture.…”

Human Gesture Recognition Based on Millimeter-Wave Radar Using Improved C3D Convolutional Neural Network

“…With the advent of the era of artificial intelligence, human gesture recognition is attracting increasing attention due to its various applications, such as intelligent human-computer interactions [1], smart security [2], assisted driving [3], entertainment [4], smart home [5][6], competent medical care [7][8], and patient health monitoring [9]. Various human gesture recognition methods have been proposed, mainly classified as wearable and non-contact sensors.…”

Lightweight Deep Symmetric Positive Definite Manifold Network for Real-Time 3D Hand Gesture Recognition

“…Hand gesture recognition is the process of detecting and classifying human hands into several categories. This task is one of the fundamental blocks in many applications such as human-robot interaction [7], video games [6], sign language interpretation [5], security and surveillance [8]. The issue of hand gesture recognition is solved by traditional methods, usually using sophisticated and expensive RGB and depth cameras.…”