6. Panorama Creation
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Hardware and Software for Panoramic Photography
ROVANIEMI UNIVERSITY OF APPLIED SCIENCES SCHOOL OF TECHNOLOGY Degree Programme in Information Technology Thesis HARDWARE AND SOFTWARE FOR PANORAMIC PHOTOGRAPHY Julia Benzar 2012 Supervisor: Veikko Keränen Approved _______2012__________ The thesis can be borrowed. School of Technology Abstract of Thesis Degree Programme in Information Technology _____________________________________________________________ Author Julia Benzar Year 2012 Subject of thesis Hardware and Software for Panoramic Photography Number of pages 48 In this thesis, panoramic photography was chosen as the topic of study. The primary goal of the investigation was to understand the phenomenon of pa- noramic photography and the secondary goal was to establish guidelines for its workflow. The aim was to reveal what hardware and what software is re- quired for panoramic photographs. The methodology was to explore the existing material on the topics of hard- ware and software that is implemented for producing panoramic images. La- ter, the best available hardware and different software was chosen to take the images and to test the process of stitching the images together. The ex- periment material was the result of the practical work, such the overall pro- cess and experience, gained from the process, the practical usage of hard- ware and software, as well as the images taken for stitching panorama. The main research material was the final result of stitching panoramas. The main results of the practical project work were conclusion statements of what is the best hardware and software among the options tested. The re- sults of the work can also suggest a workflow for creating panoramic images using the described hardware and software. The choice of hardware and software was limited, so there is place for further experiments. -
Chapter 1. Origins of Mac OS X
1 Chapter 1. Origins of Mac OS X "Most ideas come from previous ideas." Alan Curtis Kay The Mac OS X operating system represents a rather successful coming together of paradigms, ideologies, and technologies that have often resisted each other in the past. A good example is the cordial relationship that exists between the command-line and graphical interfaces in Mac OS X. The system is a result of the trials and tribulations of Apple and NeXT, as well as their user and developer communities. Mac OS X exemplifies how a capable system can result from the direct or indirect efforts of corporations, academic and research communities, the Open Source and Free Software movements, and, of course, individuals. Apple has been around since 1976, and many accounts of its history have been told. If the story of Apple as a company is fascinating, so is the technical history of Apple's operating systems. In this chapter,[1] we will trace the history of Mac OS X, discussing several technologies whose confluence eventually led to the modern-day Apple operating system. [1] This book's accompanying web site (www.osxbook.com) provides a more detailed technical history of all of Apple's operating systems. 1 2 2 1 1.1. Apple's Quest for the[2] Operating System [2] Whereas the word "the" is used here to designate prominence and desirability, it is an interesting coincidence that "THE" was the name of a multiprogramming system described by Edsger W. Dijkstra in a 1968 paper. It was March 1988. The Macintosh had been around for four years. -
A Stitching Algorithm for Automated Surface Inspection of Rotationally Symmetric Components
A Stitching Algorithm for Automated Surface Inspection of Rotationally Symmetric Components Tobias Schlagenhauf1, Tim Brander1, Jürgen Fleischer1 1Karlsruhe Institute of Technology (KIT) wbk-Institute of Production Science Kaiserstraße 12, 76131 Karlsruhe, Germany Abstract This paper provides a novel approach to stitching surface images of rotationally symmetric parts. It presents a process pipeline that uses a feature-based stitching approach to create a distortion-free and true-to-life image from a video file. The developed process thus enables, for example, condition monitoring without having to view many individual images. For validation purposes, this will be demonstrated in the paper using the concrete example of a worn ball screw drive spindle. The developed algorithm aims at reproducing the functional principle of a line scan camera system, whereby the physical measuring systems are replaced by a feature-based approach. For evaluation of the stitching algorithms, metrics are used, some of which have only been developed in this work or have been supplemented by test procedures already in use. The applicability of the developed algorithm is not only limited to machine tool spindles. Instead, the developed method allows a general approach to the surface inspection of various rotationally symmetric components and can therefore be used in a variety of industrial applications. Deep-learning-based detection Algorithms can easily be implemented to generate a complete pipeline for failure detection and condition monitoring on rotationally symmetric parts. Keywords Image Stitching, Video Stitching, Condition Monitoring, Rotationally Symmetric Components 1. Introduction The remainder of the paper is structured as follows. Section 2 reviews the current state of the art in the field of stitching. -
Megaplus Conversion Lenses for Digital Cameras
Section2 PHOTO - VIDEO - PRO AUDIO Accessories LCD Accessories .......................244-245 Batteries.....................................246-249 Camera Brackets ......................250-253 Flashes........................................253-259 Accessory Lenses .....................260-265 VR Tools.....................................266-271 Digital Media & Peripherals ..272-279 Portable Media Storage ..........280-285 Digital Picture Frames....................286 Imaging Systems ..............................287 Tripods and Heads ..................288-301 Camera Cases............................302-321 Underwater Equipment ..........322-327 PHOTOGRAPHIC SOLUTIONS DIGITAL CAMERA CLEANING PRODUCTS Sensor Swab — Digital Imaging Chip Cleaner HAKUBA Sensor Swabs are designed for cleaning the CLEANING PRODUCTS imaging sensor (CMOS or CCD) on SLR digital cameras and other delicate or hard to reach optical and imaging sur- faces. Clean room manufactured KMC-05 and sealed, these swabs are the ultimate Lens Cleaning Kit in purity. Recommended by Kodak and Fuji (when Includes: Lens tissue (30 used with Eclipse Lens Cleaner) for cleaning the DSC Pro 14n pcs.), Cleaning Solution 30 cc and FinePix S1/S2 Pro. #HALCK .........................3.95 Sensor Swabs for Digital SLR Cameras: 12-Pack (PHSS12) ........45.95 KA-11 Lens Cleaning Set Includes a Blower Brush,Cleaning Solution 30cc, Lens ECLIPSE Tissue Cleaning Cloth. CAMERA ACCESSORIES #HALCS ...................................................................................4.95 ECLIPSE lens cleaner is the highest purity lens cleaner available. It dries as quickly as it can LCDCK-BL Digital Cleaning Kit be applied leaving absolutely no residue. For cleaing LCD screens and other optical surfaces. ECLIPSE is the recommended optical glass Includes dual function cleaning tool that has a lens brush on one side and a cleaning chamois on the other, cleaner for THK USA, the US distributor for cleaning solution and five replacement chamois with one 244 Hoya filters and Tokina lenses. -
Apple Remote Desktop Administrator's Guide
Apple Remote Desktop Administrator’s Guide Version 3 K Apple Computer, Inc. © 2006 Apple Computer, Inc. All rights reserved. The owner or authorized user of a valid copy of Apple Remote Desktop software may reproduce this publication for the purpose of learning to use such software. No part of this publication may be reproduced or transmitted for commercial purposes, such as selling copies of this publication or for providing paid for support services. The Apple logo is a trademark of Apple Computer, Inc., registered in the U.S. and other countries. Use of the “keyboard” Apple logo (Option-Shift-K) for commercial purposes without the prior written consent of Apple may constitute trademark infringement and unfair competition in violation of federal and state laws. Apple, the Apple logo, AirPort, AppleScript, AppleTalk, AppleWorks, FireWire, iBook, iMac, iSight, Keychain, Mac, Macintosh, Mac OS, PowerBook, QuickTime, and Xserve are trademarks of Apple Computer, Inc., registered in the U.S. and other countries. Apple Remote Desktop, Bonjour, eMac, Finder, iCal, and Safari are trademarks of Apple Computer, Inc. Adobe and Acrobat are trademarks of Adobe Systems Incorporated. Java and all Java-based trademarks and logos are trademarks or registered trademarks of Sun Microsystems, Inc. in the U.S. and other countries. UNIX is a registered trademark in the United States and other countries, licensed exclusively through X/Open Company, Ltd. 019-0629/02-28-06 3 Contents Preface 9 About This Book 10 Using This Guide 10 Remote Desktop Help 10 Notation -
Fast Vignetting Correction and Color Matching for Panoramic Image Stitching
FAST VIGNETTING CORRECTION AND COLOR MATCHING FOR PANORAMIC IMAGE STITCHING Colin Doutre and Panos Nasiopoulos Department of Electrical and Computer Engineering The University of British Columbia, Vancouver, Canada ABSTRACT When images are stitched together to form a panorama there is often color mismatch between the source images due to vignetting and differences in exposure and white balance between images. In this paper a low complexity method is proposed to correct vignetting and differences in color Fig. 1. Two images showing severe color mismatch aligned with no between images, producing panoramas that look consistent blending (left) and multi-band blending [1] (right) across all source images. Unlike most previous methods To compensate for brightness/color differences between which require complex non-linear optimization to solve for images in panoramas, several techniques have been correction parameters, our method requires only linear proposed [1],[6]-[9]. The simplest of these is to multiply regressions with a low number of parameters, resulting in a each image by a scaling factor [1]. A simple scaling can fast, computationally efficient method. Experimental results somewhat correct exposure differences, but cannot correct show the proposed method effectively removes vignetting for vignetting, so a number of more sophisticated techniques effects and produces images that are highly visually have been developed. consistent in color and brightness. A common camera model is used in most previous work on vignetting and exposure correction for panoramas [6]-[9]. Index Terms— color correction, vignetting, panorama, A scene radiance value L is mapped to an image pixel value image stitching I, through: 1. INTRODUCTION I = f ()eV ()x L (1) A popular application of image registration techniques is to In equation (1), e is the exposure with which the image stitch together multiple photos into a panorama [1][2]. -
Robust L2E Estimation of Transformation for Non-Rigid Registration Jiayi Ma, Weichao Qiu, Ji Zhao, Yong Ma, Alan L
IEEE TRANSACTIONS ON SIGNAL PROCESSING 1 Robust L2E Estimation of Transformation for Non-Rigid Registration Jiayi Ma, Weichao Qiu, Ji Zhao, Yong Ma, Alan L. Yuille, and Zhuowen Tu Abstract—We introduce a new transformation estimation al- problem of dense correspondence is typically associated with gorithm using the L2E estimator, and apply it to non-rigid reg- image alignment/registration, which aims to overlaying two istration for building robust sparse and dense correspondences. or more images with shared content, either at the pixel level In the sparse point case, our method iteratively recovers the point correspondence and estimates the transformation between (e.g., stereo matching [5] and optical flow [6], [7]) or the two point sets. Feature descriptors such as shape context are object/scene level (e.g., pictorial structure model [8] and SIFT used to establish rough correspondence. We then estimate the flow [4]). It is a crucial step in all image analysis tasks in transformation using our robust algorithm. This enables us to which the final information is gained from the combination deal with the noise and outliers which arise in the correspondence of various data sources, e.g., in image fusion, change detec- step. The transformation is specified in a functional space, more specifically a reproducing kernel Hilbert space. In the dense point tion, multichannel image restoration, as well as object/scene case for non-rigid image registration, our approach consists of recognition. matching both sparsely and densely sampled SIFT features, and The registration problem can also be categorized into rigid it has particular advantages in handling significant scale changes or non-rigid registration depending on the form of the data. -
Programming Mac OS X: a GUIDE for UNIX DEVELOPERS
Programming Mac OS X: A GUIDE FOR UNIX DEVELOPERS KEVIN O’MALLEY MANNING Programming Mac OS X Programming Mac OS X A GUIDE FOR UNIX DEVELOPERS KEVIN O’MALLEY MANNING Greenwich (74° w. long.) For electronic information and ordering of this and other Manning books, go to www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact: Special Sales Department Manning Publications Co. 209 Bruce Park Avenue Fax: (203) 661-9018 Greenwich, CT 06830 email: [email protected] ©2003 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books they publish printed on acid-free paper, and we exert our best efforts to that end. Manning Publications Co. Copyeditor: Tiffany Taylor 209 Bruce Park Avenue Typesetter: Denis Dalinnik Greenwich, CT 06830 Cover designer: Leslie Haimes ISBN 1-930110-85-5 Printed in the United States of America 12345678910–VHG–05 040302 brief contents PART 1OVERVIEW ............................................................................. 1 1 ■ Welcome to Mac OS X 3 2 ■ Navigating and using Mac OS X 27 PART 2TOOLS .................................................................................. -
Mac OS X for Java™ Geeks by Will Iverson
[ Team LiB ] • Table of Contents • Index • Reviews • Reader Reviews • Errata Mac OS X for Java™ Geeks By Will Iverson Publisher : O'Reilly Pub Date : April 2003 ISBN : 0-596-00400-1 Pages : 296 Mac OS X for Java Geeks delivers a complete and detailed look at the Mac OS X platform, geared specifically at Java developers. Programmers using the 10.2 (Jaguar) release of Mac OS X, and the new JDK 1.4, have unprecedented new functionality available to them. Whether you are a Java newbie, working your way through Java Swing and classpath issues, or you are a Java guru, comfortable with digital media, reflection, and J2EE, this book will teach you how to get around on Mac OS X. You'll also get the latest information on how to build applications that run seamlessly, and identically, on Windows, Linux, Unix, and the Mac. [ Team LiB ] [ Team LiB ] • Table of Contents • Index • Reviews • Reader Reviews • Errata Mac OS X for Java™ Geeks By Will Iverson Publisher : O'Reilly Pub Date : April 2003 ISBN : 0-596-00400-1 Pages : 296 Copyright Preface Organization Conventions Used in This Book Comments and Questions Acknowledgments Chapter 1. Getting Oriented Section 1.1. All Those Confusing Names Section 1.2. Why Now? Chapter 2. Apple's Java Platform Section 2.1. Apple JVM Basics Section 2.2. Apple's JVM Directory Layout Section 2.3. Additional APIs and Services Section 2.4. Going Forward Chapter 3. Java Tools Section 3.1. Terminal Section 3.2. Code Editors Section 3.3. Jakarta Ant Section 3.4. -
Video Stitching for Linear Camera Arrays 1
LAI ET AL.: VIDEO STITCHING FOR LINEAR CAMERA ARRAYS 1 Video Stitching for Linear Camera Arrays Wei-Sheng Lai1;2 1 University of California, Merced [email protected] 2 NVIDIA Orazio Gallo2 [email protected] Jinwei Gu2 [email protected] Deqing Sun2 [email protected] Ming-Hsuan Yang1 [email protected] Jan Kautz2 [email protected] Abstract Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts. In this work, we propose a wide- baseline video stitching algorithm for linear camera arrays that is temporally stable and tolerant to strong parallax. Our key insight is that stitching can be cast as a problem of learning a smooth spatial interpolation between the input videos. To solve this prob- lem, inspired by pushbroom cameras, we introduce a fast pushbroom interpolation layer and propose a novel pushbroom stitching network, which learns a dense flow field to smoothly align the multiple input videos for spatial interpolation. Our approach out- performs the state-of-the-art by a significant margin, as we show with a user study, and has immediate applications in many areas such as virtual reality, immersive telepresence, arXiv:1907.13622v1 [cs.CV] 31 Jul 2019 autonomous driving, and video surveillance. c 2019. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. (a) Our stitching result (b) [19] (c) [3] (d) [12] (e) Ours Figure 1: Examples of video stitching. Inspired by pushbroom cameras, we propose a deep pushbroom stitching network to stitch multiple wide-baseline videos of dynamic scenes into a single panoramic video. -
Image Stitching for Panoramas Last Updated: 12-May-2021
Image Stitching for Panoramas Last Updated: 12-May-2021 Copyright © 2020-2021, Jonathan Sachs All Rights Reserved Contents Introduction ................................................................................................................................... 3 Taking the photographs ................................................................................................................ 4 Equipment ................................................................................................................................. 4 Use a rectilinear lens................................................................................................................. 6 Use the same camera settings for all the images ...................................................................... 6 Image overlap ........................................................................................................................... 7 Camera orientation ................................................................................................................... 7 Composition .............................................................................................................................. 7 Avoid polarizing filters ............................................................................................................... 7 Single- and Multi-row panoramas .............................................................................................. 8 Mark the beginning of each series of images ........................................................................... -
Sift Based Image Stitching
Journal of Computing Technologies (2278 – 3814) / # 14 / Volume 3 Issue 3 SIFT BASED IMAGE STITCHING Amol Tirlotkar, Swapnil S. Thakur, Gaurav Kamble, Swati Shishupal Department of Information Technology Atharva College of Engineering, University of Mumbai, India. { amoltirlotkar, thakur.swapnil09, gauravkamble293 , shishupal.swati }@gmail.com Abstract - This paper concerns the problem of image Camera. Image stitching is one of the methods that can be stitching which applies to stitch the set of images to form used to create large image by the use of overlapping FOV a large image. The process to generate one large [8]. The drawback is the memory requirement and the panoramic image from a set of small overlapping images amount of computations for image stitching is very high. In is called Image stitching. Stitching algorithm implements this project, this problem is resolved by performing the a seamless stitching or connection between two images image stitching by reducing the amount of required key having its overlapping part to get better resolution or points. First, the stitching key points are determined by viewing angle in image. Stitched images are used in transmitting two reference images which are to be merged various applications such as creating geographic maps or together. in medical fields. Most of the existing methods of image stitching either It uses a method based on invariant features to stitch produce a ‘rough’ stitch or produce a ghosting or blur effect. image which includes image matching and image For region-based image stitching algorithm detect the image merging. Image stitching represents different stages to edge, prepare for the extraction of feature points.