Search results for "Gesture recognition"
showing 10 items of 25 documents
Multidimensional Integral Imaging for Sensing, Visualization, and Recognition in Degraded Environments
2019
An overview of multidimensional integral imaging for sensing, visualization, and recognition in degraded environments is presented. Applications include 3D visualization, photon starved imaging, material inspection, IR imaging, passive depth estimation, automated human gesture recognition, and long-range imaging.
A framework for sign language sentence recognition by common sense context
2007
This correspondence proposes a complete framework for sign language recognition that integrates a commonsense engine in order to deal with sentence recognition. The proposed system is based on a multilevel architecture that allows modeling and managing of the knowledge of the recognition process in a simple and robust way. The final abstraction level of this architecture introduces the semantic context and the analysis of the correctness of a sentence given in a sequence of recognized signs. Experimentations are presented using a set of signs from the Italian sign language (LIS) for domotic applications. The implemented system maintains a high recognition rate when the set of signs grows, c…
Multidimensional optical sensing and imaging for displays, computational imaging, optical security, and healthcare
2016
In this invited paper, we present an overview of our recently published work on 3D imaging, visualization and displays, including optical security using quantum imaging principles, 3D microscopy, healthcare, automated disease identification with 3D imaging, fatigue free augmented reality 3D glasses, and optical security and authentication using photon counting for IC inspection, polarimetric photon counting 3D imaging, and 3D human gesture recognition
Deep Learning-Based Sign Language Digits Recognition From Thermal Images With Edge Computing System
2021
The sign language digits based on hand gestures have been utilized in various applications such as human-computer interaction, robotics, health and medical systems, health assistive technologies, automotive user interfaces, crisis management and disaster relief, entertainment, and contactless communication in smart devices. The color and depth cameras are commonly deployed for hand gesture recognition, but the robust classification of hand gestures under varying illumination is still a challenging task. This work presents the design and deployment of a complete end-to-end edge computing system that can accurately provide the classification of hand gestures captured from thermal images. A th…
Recognizing actions with the associative self-organizing map
2013
When artificial agents interact and cooperate with other agents, either human or artificial, they need to recognize others’ actions and infer their hidden intentions from the sole observation of their surface level movements. Indeed, action and intention understanding in humans is believed to facilitate a number of social interactions and is supported by a complex neural substrate (i.e. the mirror neuron system). Implementation of such mechanisms in artificial agents would pave the route to the development of a vast range of advanced cognitive abilities, such as social interaction, adaptation, and learning by imitation, just to name a few. We present a first step towards a fully-fledged int…
Real-Time Hand Pose Recognition Based on a Neural Network Using Microsoft Kinect
2013
The Microsoft Kinect sensor is largely used to detect and recognize body gestures and layout with enough reliability, accuracy and precision in a quite simple way. However, the pretty low resolution of the optical sensors does not allow the device to detect gestures of body parts, such as the fingers of a hand, with the same straightforwardness. Given the clear application of this technology to the field of the user interaction within immersive multimedia environments, there is the actual need to have a reliable and effective method to detect the pose of some body parts. In this paper we propose a method based on a neural network to detect in real time the hand pose, to recognize whether it…
Modular Middleware for Gestural Data and Devices Management
2017
In the last few years, the use of gestural data has become a key enabler for human-computer interaction (HCI) applications. The growing diffusion of low-cost acquisition devices has thus led to the development of a class of middleware aimed at ensuring a fast and easy integration of such devices within the actual HCI applications. The purpose of this paper is to present a modular middleware for gestural data and devices management. First, we describe a brief review of the state of the art of similar middleware. Then, we discuss the proposed architecture and the motivation behind its design choices. Finally, we present a use case aimed at demonstrating the potential uses as well as the limit…
Continuous hand openness detection using a Kinect-like device
2014
This paper presents a novel method to reproduce in real time the opening and closing gestures of a human hand, animating a three-dimensional model of it. In other works, this result can be achieved by mapping a set of significant points of a real hand on the corresponding points of the model to animate. We propose an alternative way to produce the same effect without mapping points, but using a level-based estimation of the degree of opening of the hand. The experiments have been executed using Microsoft KinectTM, but the method would work on any other Kinect-like devices (as defined herein). The results obtained are particularly encouraging and demonstrate real-time performance of the syst…
Recognition of Human Actions Through Deep Neural Networks for Multimedia Systems Interaction
2019
Nowadays, interactive multimedia systems are part of everyday life. The most common way to interact and control these devices is through remote controls or some sort of touch panel. In recent years, due to the introduction of reliable low-cost Kinect-like sensing technology, more and more attention has been dedicated to touchless interfaces. A Kinect-like devices can be positioned on top of a multimedia system, detect a person in front of the system and process skeletal data, optionally with RGBd data, to determine user gestures. The gestures of the person can then be used to control, for example, a media device. Even though there is a lot of interest in this area, currently, no consumer sy…
Real-Time Body Gestures Recognition Using Training Set Constrained Reduction
2017
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…