Panoweaver 7.20 User Manual

Total Page:16

File Type:pdf, Size:1020Kb

Panoweaver 7.20 User Manual Panoweaver 7.20 User Manual Panoweaver 7.20 User Manual.....................................................................................1 Welcome....................................................................................................................................3 Introduction............................................................................................................................ 4 What's New............................................................................................................................. 4 Edition Comparison .............................................................................................................6 Get Help...................................................................................................................................8 Install Panoweaver 7.20..................................................................................................9 System Requirements (For Windows)..........................................................................9 System Requirements (For Macintosh) .....................................................................10 Install Panoweaver 7.0 Trial Version..........................................................................10 Activate Panoweaver 7.20............................................................................................14 Purchase ................................................................................................................................14 Product Activation..............................................................................................................14 Transfer License Key.........................................................................................................16 Basic Knowledge of Panoweaver 7.20...................................................................17 About Panoweaver Project File .....................................................................................17 User Interface......................................................................................................................17 Menu Bar ...........................................................................................................................17 Image Show and Operation Area.............................................................................20 Panel ...................................................................................................................................27 Status Bar .........................................................................................................................28 My First Panorama.............................................................................................................28 Shoot Images ..................................................................................................................29 Stitch Panoramic Image ..............................................................................................30 Application ........................................................................................................................31 Use Panoweaver 7.20......................................................................................................31 Import Images ....................................................................................................................32 Stitch Panoramic Image ..................................................................................................33 Parameters Setting about Stitching........................................................................33 Basic Steps before Stitching ......................................................................................39 Stitch...................................................................................................................................41 Edit Panoramic Images....................................................................................................45 1 How to Remove Tripod.................................................................................................45 Add Hotspot to Panorama...............................................................................................47 Edit Hotspot .....................................................................................................................48 Preview Panorama .............................................................................................................51 Save Panoramic Image....................................................................................................52 Retouch Image................................................................................................................53 Print Panoramic Image ................................................................................................55 Make Virtual Tour with Tourweaver........................................................................55 Publish Panorama ..............................................................................................................56 Flash VR.............................................................................................................................60 Standalone SWF .............................................................................................................66 Easypano Virtual Tour Player ....................................................................................66 Quick Time VR.................................................................................................................69 Upload to Website..........................................................................................................70 Project ....................................................................................................................................72 Advanced Settings.............................................................................................................73 Get HDR Image...................................................................................................................74 Get HDR Image from Camera Raw File .................................................................77 Get HDR Image from Bracket Exposure................................................................78 Batch Processing [Panoweaver Batch only].............................................................82 Work Space ......................................................................................................................83 Basic Steps of Batch Processing [Panoweaver Batch only]...........................87 Batch Stitching[Panoweaver Batch only] ..............................................................90 FAQ.............................................................................................................................................92 Panorama Photography..................................................................................................93 Shoot Normal Images ......................................................................................................93 Shoot Fisheye Images......................................................................................................95 Main Photography Equipment ...................................................................................95 Workflow of Shooting Fisheye Images...................................................................98 Photograph Tips..............................................................................................................98 2 Welcome This document explains the installation and operation of Easypano Panoweaver 7.20. It is intended for both newbies and professionals who engage in online panorama and virtual tour building. Conventions and Definitions Copyright Announcement Feedback Conventions and Definitions We use the following typographical conventions and definitions in this document: Typeface or Icons Purpose Italic Used to emphasize new terms and concepts at the point where they are introduced. Also used to designate the quoted terms or menus of the software. Used to arouse the readers' attention Note towards certain operations or things they should consider. Used to offer some extra techniques on Tip how to use Panoweaver. Copyright Announcement This manual, as well as the software described in it, is furnished under license and may be used or copied only in accordance with the terms of such license. The content of this manual is furnished for informational use only, is subject to change without notice. Easypano assumes no responsibility or liability for any errors or inaccuracies that may appear in this documentation. Except as permitted by such license, no part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, recording, or otherwise, without the prior written permission of Easypano. Panoweaver 7.20 and Easypano are trademarks of Easypano Holdings Inc. Microsoft, Windows, Macintosh and Internet Explorer are registered trademarks of other Corporation. About more on license information please refer to the license agreement included in the applications. Other products mentioned in this manual have rights and marks held by their respective owners. Feedback We welcome your comments and feedback on this manual. Please send your comments to us by email: [email protected] or visit the Help
Recommended publications
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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].
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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 ...........................................................................
    [Show full text]
  • 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.
    [Show full text]
  • Shooting Panoramas and Virtual Reality
    4104_ch09_p3.qxd 6/25/03 11:17 PM Page 176 4104_ch09_p3.qxd 6/25/03 11:17 PM Page 177 Shooting Panoramas and Virtual Reality With just a little help from special software, you can extend the capabilities of your digital camera to create stunning panoramas and enticing virtual reality (VR) images. This chapter shows you how to shoot—and create— images that are not only more beautiful, but 177 ■ also have practical applications in the commer- SHOOTING PANORAMAS AND VIRTUAL REALITY cial world as well. Chapter Contents 9 Panoramas and Object Movies Shooting Simple Panoramas Extending Your View Object Movies Shooting Tips for Object Movies Mikkel Aaland Mikkel 4104_ch09_p3.qxd 6/25/03 11:18 PM Page 178 Panoramas and Object Movies Look at Figure 9.1. It’s not what it seems. This panorama is actually comprised of several images “stitched” together using a computer and special software. Because of the limitations of the digital camera’s optical system, it would have been nearly impos- sible to make this in a single shot. Panoramas like this can be printed, or with an extended angle of view and more software help, they can be turned into interactive virtual reality (VR) movies viewable on a computer monitor and distributed via the Web or on a CD. Figure 9.1: This panorama made by Scott Highton using a Nikon Coolpix 990 is comprised of 178 four adjacent images, “stitched” together using Photoshop Elements’ 2 Photomerge plug-in. ■ If you look at Figure 9.2 you’ll see another example where software was used to extend the capabilities of a digital camera.
    [Show full text]
  • Image Stitching
    Panoramic Image Mosaics Image Stitching Computer Vision CSE 576, Spring 2008 Full screen panoramas (cubic): http://www.panoramas.dk/ Richard Szeliski Mars: http://www.panoramas.dk/fullscreen3/f2_mars97.html Microsoft Research 2003 New Years Eve: http://www.panoramas.dk/fullscreen3/f1.html Richard Szeliski Image Stitching 2 Gigapixel panoramas & images Image Mosaics + + … + = Mapping / Tourism / WWT Medical Imaging Goal: Stitch together several images into a seamless composite Richard Szeliski Image Stitching 3 Richard Szeliski Image Stitching 4 Today’s lecture Readings Image alignment and stitching • Szeliski, CVAA: • motion models • Chapter 3.5: Image warping • Chapter 5.1: Feature-based alignment (in preparation) • image warping • Chapter 8.1: Motion models • point-based alignment • Chapter 8.2: Global alignment • Chapter 8.3: Compositing • complete mosaics (global alignment) • compositing and blending • Recognizing Panoramas, Brown & Lowe, ICCV’2003 • ghost and parallax removal • Szeliski & Shum, SIGGRAPH'97 Richard Szeliski Image Stitching 5 Richard Szeliski Image Stitching 6 Motion models What happens when we take two images with a camera and try to align them? Motion models • translation? • rotation? • scale? • affine? • perspective? … see interactive demo (VideoMosaic) Richard Szeliski Image Stitching 8 Image Warping image filtering: change range of image g(x) = h(f(x)) Image Warping f f h x x image warping: change domain of image g(x) = f(h(x)) f f h x x Richard Szeliski Image Stitching 10 Image Warping Parametric (global) warping
    [Show full text]
  • Robust Panoramic Image Stitching CS231A Final Report
    Robust Panoramic Image Stitching CS231A Final Report Harrison Chau Robert Karol Department of Aeronautics and Astronautics Department of Aeronautics and Astronautics Stanford University Stanford University Stanford, CA, USA Stanford, CA, USA [email protected] [email protected] Abstract— Creation of panoramas using computer vision is not a new algorithms combined in a novel way. First, an image database idea, however, most algorithms are focused on creating a panorama is created. This is done manually by taking pictures from a using all of the images in a directory. The method which will be variety of locations around the world. SIFT keypoints are then explained in detail takes this approach one step further by not found for each image. The algorithm then sorts through the requiring the images in each panorama be separated out manually. images to find keypoint matches between the images. A Instead, it clusters a set of pictures into separate panoramas based on clustering algorithm is run which separates the images into scale invariant feature matching. Then uses these separate clusters to separate panoramas, and the individual groups of images are stitch together panoramic images. stitched and mosaicked together to form separate panoramas. Keywords—Panorama; SIFT; RANSAC; Homography; II. RELATED WORK Keypoint; Stitching; Clustering A. Prior Algorithms I. INTRODUCTION Algorithms which have been used to create panoramas You travel often for work or pleasure but you have had a have been developed in the past and implemented many times. passion for photography since childhood. Over the years, you Some of these algorithms have even been optimized to run in take many different photographs at each of your destination.
    [Show full text]
  • A Method of Generating Panoramic Street Strip Image Map with Mobile Mapping System
    The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B1, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic A METHOD OF GENERATING PANORAMIC STREET STRIP IMAGE MAP WITH MOBILE MAPPING SYSTEM Chen Tianen a *, Kohei Yamamoto a, Kikuo Tachibana a a PASCO CORP. R&D CENTER, 2-8-10 Higashiyama Meguro-Ku, Tokyo 153-0043, JAPAN – (tnieah3292, kootho1810, kainka9209)@pasco.co.jp Commission I, ICWG I/VA KEY WORDS: Mobile Mapping System, Omni-Directional Camera, Laser Point Cloud, Street-Side Map, Image Stitching ABSTRACT: This paper explores a method of generating panoramic street strip image map which is called as “Pano-Street” here and contains both sides, ground surface and overhead part of a street with a sequence of 360° panoramic images captured with Point Grey’s Ladybug3 mounted on the top of Mitsubishi MMS-X 220 at 2m intervals along the streets in urban environment. On-board GPS/IMU, speedometer and post sequence image analysis technology such as bundle adjustment provided much more accuracy level position and attitude data for these panoramic images, and laser data. The principle for generating panoramic street strip image map is similar to that of the traditional aero ortho-images. A special 3D DEM(3D-Mesh called here) was firstly generated with laser data, the depth map generated from dense image matching with the sequence of 360° panoramic images, or the existing GIS spatial data along the MMS trajectory, then all 360° panoramic images were projected and stitched on the 3D-Mesh with the position and attitude data.
    [Show full text]