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R ecent film releases such as Avatar have revolutionized cinema by combining 3D technology and content production and real actors, leading to the creation of a new genre at the outset of the 2010s. The success of 3D cinema has led several major consumer electronics manufacturers to launch 3D-capable televisions and broadcasters to offer 3D content. Today's 3DTV technology is based on stereo vision, which presents left-and right-eye images through temporal or spatial multiplexing to viewers wearing a pair of glasses. The next step in 3DTV development will likely be a multiview autostereoscopic imaging system, which will record and present many pairs of video signals on a display and will not require viewers to wear glasses. 1,2 Although researchers have proposed several autostereoscopic displays, the resolution and viewing position is still limited. Furthermore, stereo and multiview technologies rely on the brain to fuse the two disparate images to create the 3D effect. As a result, such systems tend to cause eye strain, fatigue, and headaches after prolonged viewing because users are required to focus on the screen plane (accommodation) but to converge their eyes to a point in space in a different plane (convergence), producing unnatural viewing. Recent advances in digital technology have eliminated some of these human factors, but some intrinsic eye fatigue will always exist with stereoscopic 3D technology. 3 These facts have motivated researchers to seek alternative means for capturing true 3D content, most notably holography and holoscopic imaging. Due to the interference of the coherent light fields required to record holograms, their use is still limited and mostly confined to research laboratories. Holoscopic imaging (also referred to as integral imaging) in its simplest form, on the other hand, consists of a lens array mated to a digital sensor with each lens capturing perspective views of the scene. 49 In this case, the light field does not need to be coherent, so holoscopic color images can be obtained with full parallax. This conveniently lets us adopt more conventional live capture and display procedures. Furthermore, 3D holoscopic imaging offers fatigue-free viewing to more than one person, independent of the viewers' positions.Due to recent advances in theory and microlens manufacturing, 3D holoscopic imaging is becoming a practical, prospective 3D display technology and is thus attracting much interest in the 3D area. The 3D Live Immerse VideoAudio Interactive Multimedia (3D Vivant, www.3dvivant.eu) project, funded by the EU-FP7 ICT-4-1.5Networked Media and 3D Internet, has proposed advances in 3D holoscopic imaging technology for the capture, representation, processing, and display of 3D holoscopic content that overcome most of the aforementioned restrictions faced by traditional 3D technologies. This article presents our work as part of the 3D Vivant project. 3D Holoscopic Content GenerationThe 3D holoscopic imaging technique creates and represents a true volume spatial optical model of the objec...

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From the last decade, researches on human facial emotion recognition disclosed that computing models built on regression modelling can produce applicable performance. However, many systems need extensive computing power to be run that prevents its wide applications such as robots and smart devices. In this proposed system, a real-time automatic facial expression system was designed, implemented and tested on an embedded device such as FPGA that can be a first step for a specific facial expression recognition chip for a social robot. The system was built and simulated in MATLAB and then was built on FPGA and it can carry out real time continuously emotional state recognition at 30 fps with 47.44% accuracy. The proposed graphic user interface is able to display the participant video and two dimensional predict labels of the emotion in real time together.

With the rapid development of augmented reality (AR) and virtual reality (VR) technology, human-computer interaction (HCI) has been greatly improved for gaming interaction of AR and VR control. The finger micro-gesture is one of the important interactive methods for HCI applications such as in the Google Soli and Microsoft Kinect projects. However, the progress in this research is slow due to the lack of high quality public available database. In this paper, holoscopic 3D camera is used to capture high quality micro-gesture images and a new unique holoscopic 3D micro-gesture (HoMG) database is produced. The principle of the holoscopic 3D camera is based on the flys viewing system to see the objects. HoMG database recorded the image sequence of 3 conventional gestures from 40 participants under different settings and conditions. For the purpose of micro-gesture recognition, HoMG has a video subset with 960 videos and a still image subset with 30635 images. Initial micro-gesture recognition on both subsets has been conducted using traditional 2D image and video features and popular classifiers and some encouraging performance has been achieved. The database will be available for the research communities and speed up the research in this area.

Abstract:Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environment followed by a MATLAB Simulink environment that is capable of recognizing continuous facial expressions in real-time with a rate of 1 frame per second and that is implemented on a desktop PC. They have been evaluated in a public dataset, and the experimental results were promising. The dataset and labels used in this study were made from videos, which were recorded twice from five participants while watching a video. Secondly, in order to implement in real-time at a faster frame rate, the facial expression recognition system was built on the field-programmable gate array (FPGA). The camera sensor used in this work was a Digilent VmodCAM -stereo camera module. The model was built on the Atlys TM Spartan-6 FPGA development board. It can continuously perform emotional state recognition in real-time at a frame rate of 30. A graphical user interface was designed to display the participant's video in real-time and two-dimensional predict labels of the emotion at the same time.