Research on Gesture Recognition Method Based on Computer Vision Technology

Cui, Hongjian; Wang, Yixuan

doi:10.1109/cibda50819.2020.00087

Cited by 5 publications

(3 citation statements)

References 1 publication

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“…The gesture model, derived from visual imagery extracted from gesture labels and employing parametric modeling methodologies, is an abstract construct. This model is essentially categorized into two modalities: a 2D gesture model predicated on visual features and a 3D gesture model founded on skeletal attributes [17]. By employing the pertinent data pertaining to gesture acquisition and labeling, judgments regarding the correctness of the current gesture are made in accordance with stipulated criteria.…”

Section: Openpose Working Mechanismmentioning

confidence: 99%

An Interactive Application for Hand Muscle Fatigue Relief Based on Gesture Recognition

Pang,

Xing,

Tang

et al. 2024

Frontiers in Artificial Intelligence and Applications

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Prolonged use of a keyboard or mouse can lead to continuous bending and twisting of the wrist, which can lead to muscle fatigue and pain. Finger exercises can reduce the hand muscle fatigue effectively. However, the repetitive exercises will bring boring and tedious experience. In this paper, we developed a hand rehabilitation exercise system based on gesture recognition technology and gamification design, which provides a more enjoyable, personalized and effective rehabilitation experience. The hand fatigue relief system was designed with the fusion of game elements and gesture interaction, which can enhance users’ engagement and their rehabilitation motivation.

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Section: Openpose Working Mechanismmentioning

confidence: 99%

An Interactive Application for Hand Muscle Fatigue Relief Based on Gesture Recognition

Pang,

Xing,

Tang

et al. 2024

Frontiers in Artificial Intelligence and Applications

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“…The results suggest that the future development trends in this field will be deep vision sensorbased gesture recognition, multi-method cross-fusion gesture recognition, and gesture recognition based on straightforward wearable devices. [7] For the purpose of recognizing hand gestures in Japanese Sign Language (JSL), a sensor-based data acquisition glove is being developed. Five flex sensors, an Inertial Measurement Unit (IMU), and three Force Sensing Resistors (FSRs) are used to measure the amount of finger bending and hand movement data.…”

Section: Literature Surveymentioning

confidence: 99%

Exploring The Techniques and Applications of Hand Gesture Recognition for Human-Computer Interaction

Khada

2023

IJSREM

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Hand gesture controlled applications are software applications that are controlled by the user's hand movements. Hand gesture controlled applications have the potential to improve user experience by offering more intuitive and immersive ways to interact with system. Hand gesture controlled applications have a huge scope, including gaming, virtual reality, robotics, healthcare, and various other sectors. In this paper, we have combined several disparate end results of subsystems such as virtual mouse, contactless keyboard, finger counting, taking selfies, sign language, game, handling installed applications and volume control using computer vision. For implementation, we used the open-source software library OpenCV, mediapipe and pyautogui. Various hand gestures are assigned to launch and control different applications. These hand gestures are recognized using machine learning trained models, Euclidean distance formula and pixel positions. Overall, it allows humans to interact with computers through hand gestures rather than traditional input/output mechanisms such as the keyboard and mouse, improving accessibility. Key Words: Computer vision, OpenCV, hand gesture, machine learning, TensorFlow, pyautogui, mediapipe, virtual mouse, virtual keyboard, sign language, gaming.

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“…Thereafter, a technique for detecting static motions with the finger was devised. HOG extracted the features in order to generate a binary image [10].…”

Section: State Of the Art In Gesture Recognitionmentioning

confidence: 99%

Human Gesture Recognition in Computer Vision Research

Zheng

2022

SHS Web Conf.

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Human gesture recognition is a popular issue in the studies of computer vision, since it provides technological expertise required to advance the interaction between people and computers, virtual environments, smart surveillance, motion tracking, as well as other domains. Extraction of the human skeleton is a rather typical gesture recognition approach using existing technologies based on two-dimensional human gesture detection. Likewise, I t cannot be overlooked that objects in the surrounding environment give some information about human gestures. To semantically recognize the posture of the human body, the logic system presented in this research integrates the components recognized in the visual environment alongside the human skeletal position. In principle, it can improve the precision of recognizing postures and semantically represent peoples’ actions. As such, the paper suggests a potential and notion for recognizing human gestures, as well as increasing the quantity of information offered through analysis of images to enhance interaction between humans and computers.

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Research on Gesture Recognition Method Based on Computer Vision Technology

Cited by 5 publications

References 1 publication

An Interactive Application for Hand Muscle Fatigue Relief Based on Gesture Recognition

An Interactive Application for Hand Muscle Fatigue Relief Based on Gesture Recognition

Exploring The Techniques and Applications of Hand Gesture Recognition for Human-Computer Interaction

Human Gesture Recognition in Computer Vision Research

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