SIXTH SENSE TECHNOLOGY 1.INTRODUCTION Although miniaturized versions of computers help us to connect to the digital world even while we are travelling there aren’t any device as of now which gives a direct link between the digital world and our physical interaction with the real world. Usually the information’s are stored traditionally on a paper or a digital storage device. Sixth sense technology helps to bridge this gap between tangible and non-tangible
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ABSTRACT NOTE DETECTION USING COMPUTER VISION Cameras turn out to be a standard feature of PC hardware and a mobile device. Thus computer vision is expanding its horizon from a niche tool to an increasingly common device for a diverse range of applications. At its core‚ computer vision is developed upon the fields of mathematics‚ physics‚ biology‚ engineering‚ and of course computer science. Nowadays‚ there are more casual developers opening the door to many new application and innovation due
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Feature Extraction and Image Processing Dedication We would like to dedicate this book to our parents: To Gloria and Joaquin Aguado‚ and to Brenda and the late Ian Nixon. Feature Extraction and Image Processing Second edition Mark S. Nixon Alberto S. Aguado Amsterdam • Boston • Heidelberg • London • New York • Oxford Paris • San Diego • San Francisco • Singapore • Sydney • Tokyo Academic Press is an imprint of Elsevier Academic Press is an imprint of Elsevier Linacre House‚ Jordan
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____________________________ Date : ____________________________ ACKNOWLEDGEMENT I would like to give my special thanks to my supervisor‚ Mr. Tou Jing Yi for guide and support me throughout my research on FYP. He has provided me a chance to engage in computer vision field‚ which is a very interesting IT field that yet to be discovered. Without his guidance and support‚ I would not be able to deliver this project. I really appreciate his guidance and support. Thanks. I would also like to thanks Mr. Ho Wing
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Master Thesis Secure Face Recognition and User Access !!! DRAFT !!! Scientific Coordinator Prof. Ion IVAN‚ Ph.D. Graduate Valentin-Petruţ SUCIU - Bucharest 2011 - Contents Introduction 1. Machine Based Facial Detection and Recognition 1.1 Computer Vision 1.2 Object Detection 1.3 Image Quality 1.4 Facial Recognition Approaches 2. Proposed Solution 2.1 Data Preparation 2.2 Recognition Logic and Algorithms 2.3 Database Structure 2.4 Front End Applications 2.5 Defining Tests 3. The Implementation
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Foundations and Trends R in Robotics Vol. 1‚ No. 1 (2010) 1–78 c 2009 D. Kragic and M. Vincze DOI: 10.1561/2300000001 Vision for Robotics By Danica Kragic and Markus Vincze Contents 1 Introduction 1.1 Scope and Outline 2 4 7 7 9 12 17 18 27 32 35 42 44 48 49 52 2 Historical Perspective 2.1 2.2 2.3 Early Start and Industrial Applications Biological Influences and Affordances Vision Systems 3 What Works 3.1 3.2 3.3 3.4 3.5 3.6 Object Tracking and Pose Estimation Visual Servoing–Arms and Platforms
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images‚ its performance can be further improved if video stream is available. Main Body Text Introduction The advances of computing technology has facilitated the development of real-time vision modules that interact with humans in recent years. Examples abound‚ particularly in biometrics and human computer interaction as the information contained in faces needs to be analyzed for systems to react accordingly. For biometric systems that use faces as non-intrusive input modules‚ it is imperative
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Real Time 3D Face Alignment with Random Forests-based Active Appearance Models Gabriele Fanelli‚ Matthias Dantone‚ Luc Van Gool Computer Vision Laboratory‚ ETH Zurich‚ Sternwartstrasse 7‚ 8092 Zurich‚ Switzerland {fanelli/dantone/vangool}@vision.ee.ethz.ch Abstract— Many desirable applications dealing with automatic face analysis rely on robust facial feature localization. While extensive research has been carried out on standard 2D imagery‚ recent technological advances made the acquisition
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synthetic elements are rendered and aligned in the scene in an accurate and visually acceptable way. In order to address these issues a real-time‚ robust and efficient 3D model-based tracking algorithm is proposed for a ’video see through’ monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here‚ non-linear pose computation is formulated by means of a virtual
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Image Processing‚ Analysis‚ and Machine Vision Second Edition Milan Sonka Vaclav Hlavac Roger Boyle Contents List of algorithms xiii List of symbols and abbreviations xvii Preface xix Course contents xxiii 1 Introduction 1 1.1 Summary 1.2 Exercises 1.3 References 8 8 9 2 The digitized image and its properties 2.1 Basic concepts 2.1.1 Image functions 2.1.2 The Dirac distribution and convolution 2.1.3 The Fourier transform 2.1.4 Images as
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