Hand Gesture Recognition
44 papers with code • 18 benchmarks • 14 datasets
Hand gesture recognition (HGR) is a subarea of Computer Vision where the focus is on classifying a video or image containing a dynamic or static, respectively, hand gesture. In the static case, gestures are also generally called poses. HGR can also be performed with point cloud or joint hand data.
Benchmarks
These leaderboards are used to track progress in Hand Gesture Recognition
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Datasets
EgoGesture
SHREC
NVGesture
Jester (Gesture Recognition)
IPN Hand
VIVA
RWTH-PHOENIX Handshapes dev set
OREBA
LSA16
Latest papers with no code
Agile gesture recognition for capacitive sensing devices: adapting on-the-job
However, there is growing demand for gesture recognition technology that can be implemented on low-power devices using limited sensor data instead of high-dimensional inputs like hand images.
SimplyMime: A Control at Our Fingertips
This paper presents a novel system, named SimplyMime, which aims to eliminate the need for multiple remote controls for consumer electronics and provide the user with intuitive control without the need for additional devices.
Deep Attention Network for Enhanced Hand Gesture Recognition System
Available datasets were collected to train the deep neural network architecture to create a gesture recognition system.
PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural Sensors
Conventional image sensors digitize high-resolution images at fast frame rates, producing a large amount of data that needs to be transmitted off the sensor for further processing.
Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM
In the past few years, more and more AI applications have been applied to edge devices.
IMU-based Modularized Wearable Device for Human Motion Classification
The results of the case studies show that distance-measure-based and PCA-based dimension reduction will significantly improve human motion identification accuracy.
EvHandPose: Event-based 3D Hand Pose Estimation with Sparse Supervision
Experiments on EvRealHands demonstrate that EvHandPose outperforms previous event-based methods under all evaluation scenes, achieves accurate and stable hand pose estimation with high temporal resolution in fast motion and strong light scenes compared with RGB-based methods, generalizes well to outdoor scenes and another type of event camera, and shows the potential for the hand gesture recognition task.
Real-Time Hand Gesture Identification in Thermal Images
Hand gesture-based human-computer interaction is an important problem that is well explored using color camera data.
Visual motion analysis of the player's finger
This work is about the extraction of the motion of fingers, in their three articulations, of a keyboard player from a video sequence.
Hand Gesture Recognition through Reflected Infrared Light Wave Signals
In this study, we present a wireless (non-contact) gesture recognition method using only incoherent light wave signals reflected from a human subject.
