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29 articles for “Gesture recognition”
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Controlling Media Player Through Hand Gesture Recognition System Using CNN and RNN Models
Abstract: Artificial intelligence markup language (AIML) project represents a pioneering endeavor in the realm of media player control through hand gesture recognition, merging advanced technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN). By harnessing the image analysis capabilities of CNN, our system ensures accurate, real-time detection, and interpretation of intricate hand gestures, enabling users to interact with their media content naturally and seamlessly. What sets our project apart …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 29–34 Read article
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Hand Gesture Recognition Systems: A Review of Vision-based and Sensor-based Approaches
Abstract: With many real-world uses, such as sign language translation and human-computer interaction, hand gesture detection is a crucial area of study in the science of computer vision. In this study, we propose a Convolutional Neural Network (CNN) model that uses real-time camera images to recognise hand gestures. A collection of hand motion photographs spanning the English alphabet (A-Z) was gathered, and the images were pre-processed to exclude any backdrop and …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Implementation of Human Gesture Recognition Using CNN
Abstract: A gesture popularity system based entirely on convolutional neural networks (CNNs). Preprocessing techniques include segmentation, polygonal approximation, contour construction, morphological filters, and resource characteristic extraction. Various convolutional neural networks are employed for training and testing, with results compared to existing architectures and protocols. All generated measurements and convergence graphs produced at any point during education are examined and contested in order to verify the reliability of the approach offered. Our …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 24–37 Read article
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Real-Time Gesture Recognition with Convolutional Neural Networks
Abstract: Sign language detection plays a pivotal role in bridging communication barriers for the deaf and hard of hearing community. An extensive investigation on the use of convolutional neural networks (CNNs) for sign language recognition is presented in this article. Leveraging the power of deep learning, our research aims to develop an accurate and efficient system capable of recognizing and classifying sign language gestures in real-time. The report begins with an …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 12–18 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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Brain And Gesture Controlled Assistive System For Physically Challenged Individuals
Abstract: Assistive communication technologies are essential for improving the independence of individuals with physical and sensory disabilities. This paper presents the design and implementation of a multimodal assistive system that integrates brain signal acquisition and gesture recognition for real- time communication. The system utilizes an Electroencephalography (EEG) sensor to capture neural activity and a PAJ7620 gesture sensor along with an ADXL335 accelerometer to detect hand movements. The acquired signals are processed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 Read article
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Revolutionary Cursor Control Systems: Enhancing Human-Computer Interaction
Abstract: This project delves into leveraging artificial intelligence within virtual mouse systems to elevate human-computer interaction. The main objective is to improve user experience, increase efficiency, and introduce new ways of interaction. Employing artificial intelligence techniques such as computer vision, gesture recognition and speech recognition, the virtual mouse system adeptly tracks hand movements, interprets voice commands, recognizes gestures, and processes user inputs for seamless interactions. Tailoring features for design, gaming, accessibility, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 45–52 Read article
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Gesture-Based Virtual HCI: Enhancing Computer Interaction
Abstract: In a time when human-computer interaction (HCI) is changing quickly, generating user-friendly interfaces is essential. This paper presents a new technique to HCI using virtual mouse and keyboard systems based on gesture recognition. This system replaces classical input devices by permitting users to control their computers with hand gestures using computer vision techniques. We created an optical mouse and keyboard technique that can recognize hand gestures recorded by a regular …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 2, 2024 Read article
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Hand-Tracking-Based Mouse Control for Touchless Human-Computer Interaction: Feasibility and Future Enhancement
Abstract: This paper presents a novel approach to human-computer interaction through a hand-tracking-based mouse control system using computer vision. The system utilizes OpenCV, MediaPipe, and the Cvzone Hand Tracking Module to identify and monitor hand movements in real-time. By utilizing hand landmarks, the system maps finger positions to cursor movement and enables essential functions such as clicking, scrolling, and double-clicking. The primary motivation for developing this system is to create a …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 18–25 Read article
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Sign Talk for Blind and Deaf Translating Hand Gestures into Audible and Textual Communication
Abstract: Sign language serves as a vital communication method for individuals who are deaf or have hearing impairments. It relies on hand gestures, facial cues, and body language to convey messages and express meaning. However, many people who do not know sign language find it hard to communicate with sign language users. The latest progress in artificial intelligence and computing has enabled the creation of systems that can automatically recognize sign …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 20–26 Read article
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A Study of ROI Based Sign Language to Text Translation in Real Time Using Deep Learning
Abstract: Since sign language is their primary form of communication, it plays a significant role in the lives of hearing and speech disabled people. However, since not everyone is conversant in sign language, it is challenging for the disabled to interact with others daily. Sign language is made up of a variety of hand gestures that may stand in for a wide range of words and sentiments. The purpose of this …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Generic Virtual Mouse
Abstract: The mouse and keyboard have been replaced by new input mechanisms brought about by the quick development of Human-Computer Interaction (HCI). Using computer vision and deep learning techniques, this study explores the possibility of replacing actual mouse inputs in a computer system with hand gestures. We created a virtual mouse system that uses a normal webcam to record hand motions. Computer vision algorithms then process these gestures to handle mouse …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Air Touch Mouse Interface
Abstract: The “Air Touch Mouse Interface” introduces a groundbreaking method for human–computer interaction (HCI) by utilizing hand gestures captured through web cameras to control cursor movements without physical input devices. This project investigates the feasibility and effectiveness of employing image processing techniques to interpret hand gestures as mouse inputs, thereby enhancing the accessibility and versatility of computing interfaces. By eliminating the dependency on traditional mice and mouse pads, the proposed interface …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 1–16 Read article
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Hand Gesture Control Robotic Arm using OpenCV and NodeMCU
Abstract: In this research paper, an innovative method is proposed for controlling a robotic arm through the use of hand gestures, utilizing the advanced features of Node MCU and OpenCV. By bringing together these cutting-edge technologies, the system enables seamless real-time communication and image processing between the user and the robotic arm. The process involves capturing hand gestures through a camera and using the powerful OpenCV library to identify and interpret …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 1, 2024 Read article
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Gesture-Based Cursor Control: A Comprehensive Review of Techniques and Applications
Abstract: Although hand gesture detection for man-machine interfaces has advanced recently, many systems still have issues with background and lighting. We have developed a rapid motion history image-based system to categorize dynamic hand motions and a face detection method to adaptively detect skin color. For the up, down, left-, and right-hand gesture classifiers, four sets of haar-like directional patterns were trained. To operate different household appliances, six hand gestures were defined, …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 9–13 Read article
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A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV
Abstract: This venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 35–40 Read article
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An Efficient Vision-Based Algorithm for Hand Pose Estimation and Cursor Control
Abstract: Conventional input devices like the keyboard and mouse are no longer necessary because gestures are becoming more popular as the most natural way to interact with computers. This project has demonstrated a novel real-time system that lets users control their computer cursors using simple hand gestures. The system facilitates an easy operation for us in terms of the use of a cursor by using techniques and hand mark detections. The …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 24–35 Read article
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Arduino Empowered: Smart Glove Review and Analysis
Abstract: In recent years, there has been a growing interest in wearable technology, particularly in the realm of human-computer interaction (HCI). Smart gloves, equipped with various sensors and actuators, have emerged as a promising interface for facilitating seamless interaction between humans and digital devices. This paper presents the development of Arduino-based smart gloves designed to augment conventional HCI methods by incorporating gesture recognition and tactile feedback capabilities. The smart gloves feature …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Integrating Deep Learning and Computer Vision for Recognizing American Sign Language
Abstract: The only way the hearing-impaired community can exchange ideas is by utilizing non-verbal communication. The main challenge, however, is that the non-impaired community, which may not comprehend non-verbal communication, would struggle to communicate effectively with this group, and vice versa. The project is purposely devised to admit unwilling and dumb societies to transport ideas and connect with the organization. It aims to bridge the gap between the hearing- and speech-impaired …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 10–17 Read article