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Borko Furht - Handbook of Augmented Reality

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Borko Furht Handbook of Augmented Reality
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Augmented Reality (AR) refers to the merging of a live view of the physical, real world with context-sensitive, computer-generated images to create a mixed reality. Through this augmented vision, a user can digitally interact with and adjust information about their surrounding environment on-the-fly. Handbook of Augmented Reality provides an extensive overview of the current and future trends in Augmented Reality, and chronicles the dramatic growth in this field. The book includes contributions from world expert s in the field of AR from academia, research laboratories and private industry. Case studies and examples throughout the handbook help introduce the basic concepts of AR, as well as outline the Computer Vision and Multimedia techniques most commonly used today. The book is intended for a wide variety of readers including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students. This book can also be beneficial for business managers, entrepreneurs, and investors.

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Part 1
TECHNOLOGIES
Borko Furht (ed.) Handbook of Augmented Reality 10.1007/978-1-4614-0064-6_1 Springer Science+Business Media, LLC 2011
1. Augmented Reality: An Overview
Julie Carmigniani 1
(1)
Department of Computer and Electrical Engineering and Computer Sciences, Florida Atlantic University, Boca Raton, Florida, USA
(2)
Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, USA
Julie Carmigniani (Corresponding author)
Email:
Borko Furht
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Abstract
We define Augmented Reality (AR) as a real-time direct or indirect view of a physical real-world environment that has been enhanced/ augmented by adding virtual computer-generated information to it [1]. AR is both interactive and registered in 3D as well as combines real and virtual objects. Milgrams Reality-Virtuality Continuum is defined by Paul Milgram and Fumio Kishino as a continuum that spans between the real environment and the virtual environment comprise Augmented Reality and Augmented Virtuality (AV) in between, where AR is closer to the real world and AV is closer to a pure virtual environment, as seen in Fig.1.1 [2].
Introduction
We define Augmented Reality (AR) as a real-time direct or indirect view of a physical real-world environment that has been enhanced/ augmented by adding virtual computer-generated information to it [].
Fig 11 Milgrams reality-virtuality continuum Augmented Reality aims at - photo 1
Fig. 1.1
Milgrams reality-virtuality continuum []
Augmented Reality aims at simplifying the users life by bringing virtual information not only to his immediate surroundings, but also to any indirect view of the real-world environment, such as live-video stream. AR enhances the users perception of and interaction with the real world. While Virtual Reality (VR) technology or Virtual Environment as called by Milgram, completely immerses users in a synthetic world without seeing the real world, AR technology augments the sense of reality by superimposing virtual objects and cues upon the real world in real time. Note that, as Azuma et al. [] also considered AR applications that require removing real objects from the environment, which are more commonly called mediated or diminished reality , in addition to adding virtual objects. Indeed, removing objects from the real world corresponds to covering the object with virtual information that matches the background in order to give the user the impression that the object is not there. Virtual objects added to the real environment show information to the user that the user cannot directly detect with his senses. The information passed on by the virtual object can help the user in performing daily-tasks work, such as guiding workers through electrical wires in an aircraft by displaying digital information through a headset. The information can also simply have an entertainment purpose, such as Wikitude or other mobile augmented reality. There are many other classes of AR applications, such as medical visualization, entertainment, advertising, maintenance and repair, annotation, robot path planning, etc.
History
The first appearance of Augmented Reality (AR) dates back to the 1950s when Morton Heilig, a cinematographer, thought of cinema is an activity that would have the ability to draw the viewer into the onscreen activity by taking in all the senses in an effective manner. In 1962, Heilig built a prototype of his vision, which he described in 1955 in The Cinema of the Future, named Sensorama, which predated digital computing [] predicts that AR technologies will emerge more fully within the next 45 years; and, as to confirm that prediction, camera systems that can analyze physical environments in real time and relate positions between objects and environment are developed the same year. This type of camera system has become the basis to integrate virtual objects with reality in AR systems. In the following years, more and more AR applications are developed especially with mobile applications, such as Wikitude AR Travel Guide launched in 2008, but also with the development of medical applications in 2007. Nowadays, with the new advances in technology, an increasing amount of AR systems and applications are produced, notably with MIT 6th sense prototype and the release of the iPad 2 and its successors and competitors, notably the Eee Pad, and the iPhone 4, which promises to revolutionize mobile AR.
Fig 12 Ivan Sutherlands HMD Augmented Reality Technologies 31 - photo 2
Fig. 1.2
Ivan Sutherlands HMD []
Augmented Reality Technologies
3.1 Computer Vision Methods in AR
Computer vision renders 3D virtual objects from the same viewpoint from which the images of the real scene are being taken by tracking cameras. Augmented reality image registration uses different method of computer vision mostly related to video tracking. These methods usually consist of two stages: tracking and reconstructing/recognizing. First, fiducial markers, optical images, or interest points are detected in the camera images. Tracking can make use of feature detection, edge detection, or other image processing methods to interpret the camera images. In computer vision, most of the available tracking techniques can be separated in two classes: feature-based and model-based []. Once a connection is made between the 2D image and 3D world frame, it is possible to find the camera pose by projecting the 3D coordinates of the feature into the observed 2D image coordinates and by minimizing the distance to their corresponding 2D features. The constraints for camera pose estimation are most often determined using point features. The reconstructing/recognizing stage uses the data obtained from the first stage to reconstruct a real world coordinate system.
Assuming a calibrated camera and a perspective projection model, if a point has coordinates ( x , y , z ) T in the coordinate frame of the camera, its projection onto the image plane is Handbook of Augmented Reality - image 3 .
In point constraints, we have two principal coordinate systems, as illustrated in Fig., the world coordinate system W and the 2D image coordinate system. Let p i ( x i , y i , z i ) T , where i =1,, n , with n 3, be a set of 3D non-collinear reference points in the world frame coordinate and q i ( x i , y i , z i ) T be the corresponding camera-space coordinates, p i and q i are related by the following transformation:
11 where 12 are a rotation matrix and a translation vector - photo 4
(1.1)
where
12 are a rotation matrix and a translation vector respectively Fig - photo 5
(1.2)
are a rotation matrix and a translation vector, respectively.
Fig 13 Point constraints for the camera pose problem adapted from Let - photo 6
Fig. 1.3
Point constraints for the camera pose problem adapted from []
Let the image point h i (ui,vi,1)T be the projection of p i on the normalized image plane. The collinearity equation establishing the relationship between h i and p i using the camera pinhole is given by:
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