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Gestures

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Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.

Sensors (Basel, Switzerland)
Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of var...

Hand Pose Understanding With Large-Scale Photo-Realistic Rendering Dataset.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Hand pose understanding is essential to applications such as human computer interaction and augmented reality. Recently, deep learning based methods achieve great progress in this problem. However, the lack of high-quality and large-scale dataset pre...

A Deep Learning Framework for Recognizing Both Static and Dynamic Gestures.

Sensors (Basel, Switzerland)
Intuitive user interfaces are indispensable to interact with the human centric smart environments. In this paper, we propose a unified framework that recognizes both static and dynamic gestures, using simple RGB vision (without depth sensing). This f...

Footballer Action Tracking and Intervention Using Deep Learning Algorithm.

Journal of healthcare engineering
Fédération Internationale de Football Association is the governing body of the football world cup. The international tournament of football requires extensive training of all football players and athletes. In the training process of footballers, play...

A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance.

Sensors (Basel, Switzerland)
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...

Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research...

Wearable Sensor-Based Sign Language Recognition: A Comprehensive Review.

IEEE reviews in biomedical engineering
Sign language is used as a primary form of communication by many people who are Deaf, deafened, hard of hearing, and non-verbal. Communication barriers exist for members of these populations during daily interactions with those who are unable to unde...

An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.

Sensors (Basel, Switzerland)
In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG...

Sensor Fusion of Motion-Based Sign Language Interpretation with Deep Learning.

Sensors (Basel, Switzerland)
Sign language was designed to allow hearing-impaired people to interact with others. Nonetheless, knowledge of sign language is uncommon in society, which leads to a communication barrier with the hearing-impaired community. Many studies of sign lang...

Introducing the NEMO-Lowlands iconic gesture dataset, collected through a gameful human-robot interaction.

Behavior research methods
This paper describes a novel dataset of iconic gestures, together with a publicly available robot-based elicitation method to record these gestures, which consists of playing a game of charades with a humanoid robot. The game was deployed at a scienc...