Introduction to Real Time Gesture

What is/are Real Time Gesture?

Real Time Gesture - Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. ^[1] We propose SonicASL, a real-time gesture recognition system that can recognize sign language gestures on the fly, leveraging front-facing microphones and speakers added to commodity earphones worn by someone facing the person making the gestures. ^[2] Online motion prediction and real-time gesture recognition are also essential to develop a safe cooperation system in a decentralized manner with non-connected vehicles. ^[3] To a certain extent, the invalid gesture data is filtered, and an effective gesture feature description is established for real-time gesture recognition. ^[4] Thereafter, a conversation interface was built in Django using this model for the real-time gesture to speech conversion and vice versa. ^[5] Our system implements a neuro-inspired hyperdimensional computing algorithm locally for real-time gesture classification, as well as model training and updating under variable conditions such as different arm positions and sensor replacement. ^[6] In this paper, we propose a real-time gesture recognition model based on a feedforward artificial neural network for surface electromyography (sEMG) signals, which contains four processes: pre-processing, feature extraction, classification, and post-processing. ^[7] The proposed gesture recognition method was tested by simulation and real-time gesture recognition experiment. ^[8] To reduce driver distraction, the real-time gesture recognition system for ADAS is aimed to simplify and enhance the interaction between human and computer by implementing the vision-based technique that allows driver to interact with the vehicle infotainment system functions using natural mid-air hand gestures. ^[9] This work builds towards a real-time gesture generator which performs gestures that effectively convey rich communicative functions. ^[10] A Robotiq 2F-85 Gripper was finally used for real-time gesture-based control, with synthetic EMG data augmentation remarkably improving gesture recognition accuracy, from 68. ^[11] The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. ^[12] The aim of this work is to create a full-fledged program for implementing a real-time gesture recognition algorithm using computer vision and machine learning. ^[13] Real-time gesture recognition is possible with this programme. ^[14] These sensors capture the real time gestures made by the user. ^[15] This paper deals with real time gesture recognition and writing alphanumeric letters over the air using fingertip. ^[16] Recently, with the developments of new technologies and the large availability of inexpensive depth sensors, real time gesture recognition has been faced by using depth information and avoiding the limitations due to complex background and lighting situations. ^[17]

real time gesture recognition

This paper deals with real time gesture recognition and writing alphanumeric letters over the air using fingertip. ^[1] Recently, with the developments of new technologies and the large availability of inexpensive depth sensors, real time gesture recognition has been faced by using depth information and avoiding the limitations due to complex background and lighting situations. ^[2]