Related papers: ImAiR: Airwriting Recognition framework using Imag…
Airwriting Recognition is the task of identifying letters written in free space with finger movement. Electromyography (EMG) is a technique used to record electrical activity during muscle contraction and relaxation as a result of movement…
Airwriting Recognition is the problem of identifying letters written in free space with finger movement. It is essentially a specialized case of gesture recognition, wherein the vocabulary of gestures corresponds to letters as in a…
Airwriting Recognition refers to the problem of identification of letters written in space with movement of the finger. It can be seen as a special case of dynamic gesture recognition wherein the set of gestures are letters in a particular…
Most online handwriting recognition systems require the use of specific writing surfaces to extract positional data. In this paper we present a online handwriting recognition system for word recognition which is based on inertial…
This paper presents a novel approach, called AirScript, for creating, recognizing and visualizing documents in air. We present a novel algorithm, called 2-DifViz, that converts the hand movements in air (captured by a Myo-armband worn by a…
The recent advancement in technology breaks the barriers to communication between users and computers. The communication between humans and computers includes emotion and gesture recognition. Emotions can be recognized on the face of humans…
Air-writing is the process of writing characters or words in free space using finger or hand movements without the aid of any hand-held device. In this work, we address the problem of mid-air finger writing using web-cam video as input. In…
Gestures are an integral part of our daily interactions with the environment. Hand gesture recognition (HGR) is the process of interpreting human intent through various input modalities, such as visual data (images and videos) and…
Many mobile systems and wearable devices, such as Virtual Reality (VR) or Augmented Reality (AR) headsets, lack a keyboard or touchscreen to type an ID and password for signing into a virtual website. However, they are usually equipped with…
Handwriting recognition (HWR) using inertial measurement unit (IMU) data remains challenging due to variations in writing styles and the limited availability of datasets. Previous approaches often struggle with handwriting from unseen…
Air-writing refers to virtually writing linguistic characters through hand gestures in three-dimensional space with six degrees of freedom. This paper proposes a generic video camera-aided convolutional neural network (CNN) based…
Millimeter-wave (mmWave) radar-based gesture recognition is gaining attention as a key technology to enable intuitive human-machine interaction. Nevertheless, the significant challenge lies in obtaining large-scale, high-quality mmWave…
Hand gestures are an intuitive, socially acceptable, and a non-intrusive interaction modality in Mixed Reality (MR) and smartphone based applications. Unlike speech interfaces, they tend to perform well even in shared and public spaces.…
In this paper, we introduce a new benchmark dataset for the challenging writing in the air (WiTA) task -- an elaborate task bridging vision and NLP. WiTA implements an intuitive and natural writing method with finger movement for…
In this paper, a method for Automatic Image Registration (AIR) through histogram is proposed. Automatic image registration is one of the crucial steps in the analysis of remotely sensed data. A new acquired image must be transformed, using…
We introduce AirWare, an in-air hand-gesture recognition system that uses the already embedded speaker and microphone in most electronic devices, together with embedded infrared proximity sensors. Gestures identified by AirWare are…
This paper presents a novel approach to the digital signing of electronic documents through the use of a camera-based interaction system, single-finger tracking for sign recognition, and multi commands executing hand gestures. The proposed…
Static and dynamic hand movements are basic way for human-machine interactions. To recognize and classify these movements, first these movements are captured by the cameras mounted on the augmented reality (AR) or virtual reality (VR)…
While the efficacy of deep learning models heavily relies on data, gathering and annotating data for specific tasks, particularly when addressing novel or sensitive subjects lacking relevant datasets, poses significant time and resource…
IMUs are gaining significant importance in the field of hand gesture analysis, trajectory detection and kinematic functional study. An Inertial Measurement Unit (IMU) consists of tri-axial accelerometers and gyroscopes which can together be…