Hand gesture recognitionHand pose estimationHand shape estimation2022 Elsevier LtdEstimating the 3D pose of a hand from a 2D image is a well-studied problem and a requirement for several real-life applications such as virtual reality, augmented reality, and hand gesture recognition. Currently, ...
New class "no_gesture" with domain-specific natural hand postures was addad (2,164samples, divided by train/val/test containing 1,464, 200, 500 images, respectively) Extra classno_gesturecontains200,390bounding boxes Added new models for gesture detection, hand detection and full-frame classific...
Their approach involved extracting 3D information from depth images and generating additional data from various perspectives to simulate realistic sign gestures. The system then processed data from each perspective and provided the final prediction for gesture recognition. The experimental results, based on...
Hand Gesture Recognition using CNN Overview This project is a Convolutional Neural Network (CNN) designed to classify hand gesture images into multiple categories. The model is built using TensorFlow and Keras, and it includes layers such as convolutional layers, max-pooling layers, dropout layers, ...
Analysis of dynamic images naturally will yield more accurate recognition than that of a single static image. Gestures are recognized in the context of entire image sequences of non-constant lengths. Using an HMM for gesture recognition is advantageous because it is analogous to human performance ...
Since no online database of "Bharatanatyam" gestures is available to the public for research purposes, a customised database has been built with 900 images, consisting of 15 instances for each hand gesture. In this work, Chain Codes and Histogram of Oriented Gradients (HOG) are proposed for...
sequential imageslog-polar mappinggesture recognitionThe goal of this study is to construct a human-machine communication system. In the present study, we propose a technique to estimate the motion and position of human hand from a monocular camera, so as to extract motion parametors and ...
Wearable devices that monitor muscle activity based on surface electromyography could be of use in the development of hand gesture recognition applications. Such devices typically use machine-learning models, either locally or externally, for gesture classification. However, most devices with local processi...
Hand gesture datasetHand gesture recognitionPose-basedMotion-basedHuman–computer interactionThe use of hand gestures offers an alternative to the commonly used human–computer interfaces (i.e. keyboard, mouse, gamepad, voice, etc.), providing a more intuitive way of navigating among menus and in ...
- 手势识别:Hand Gesture Recognition - 动作识别:Action Recognition - 手势估计方法:生成方法和判别方法 1.5.1 生成方法(Generative Methods) 生成方法(基于模型)(Generative mthods: model-based) - 步骤:首先,创建大量的手势;然后,选择一个最匹配当前深度图像的手势 ...