With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands as an input device is an attractive method for providing natural Human Computer Interaction which has evolved from text-based interfaces through 2D graphical-based in...

Sleep pattern and posture recognition have become of great interest for a diverse range clinical applications. Autonomous constant monitoring sleep postures provides useful information reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, pressure sensors, which not only expensive but also intrusive in nature, uncomfortable to use. We propose an unobtru...

This paper presents a novel approach to human body posture recognition based on the MPEG-7 contour-based shape descriptor and the widely used projection histogram. A combination of them was used to recognize the main posture and the view of a human based on the binary object mask obtained by the segmentation process. The recognition is treated as a typical pattern recognition task and is carrie...

Even after more than two decades of input devices development, many people still find the interaction with computers an uncomfortable experience. Efforts should be made to adapt computers to our natural means of communication: speech and body language. The PUI paradigm has emerged as a post-WIMP interface paradigm in order to cover these preferences. The aim of this paper is the proposal of a r...

Besides the emergence of many input devices and sensors, they are still unable to provide good and simple recognition of human postures and gestures. The recognition using simple algorithms implemented on top of these devices (like the Kinect) enlarges use cases for these gestures and postures to newer domains and systems. Our methods cuts the needed computation and allow the integration of oth...

component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these wo...

Hand detection is a key step in the pre-processing stage of many computer vision tasks because human hands are involved activity. Some examples such hand posture estimation, gesture recognition, activity analysis, and other as these. Human have wide range motion change their appearance lot different ways. This makes it hard to identify some crowded place, can move In this investigation, we prov...

We propose a method for extracting 3D position and posture of hands with stereo cameras. The main contribution of our research is that our method enables to track the position and posture in mobile environments by using stereo cameras. The hand is often observed with many occluded regions, since the hand has many joints. In previous methods, many cameras are required to extract the position and...

Given the success of convolutional neural networks (CNNs) during recent years in numerous object recognition tasks, it seems logical to further extend their applicability to the treatment of three-dimensional data such as point clouds provided by depth sensors. To this end, we present an approach exploiting the CNN’s ability of automated feature generation and combine it with a novel 3D feature...

Abstract A high-fidelity digital representation of (part of) the human body is a key enabler for integrating humans in twin. Among different parts body, building model hand can be challenging task due to posture deviations among collected scans. In this article, we proposed invariant statistical shape (SSM) based on 59 3D scans hands. First, were spatially aligned using Möbius sphere-based algo...