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Panoramas Shoot with the Camera Positioned Vertically As This Will Give the Photo Merging Software More Wriggle-Room in Merging the Images
P a n o r a m a s What is a Panorama? A panoramic photo covers a larger field of view than a “normal” photograph. In general if the aspect ratio is 2 to 1 or greater then it’s classified as a panoramic photo. This sample is about 3 times wider than tall, an aspect ratio of 3 to 1. What is a Panorama? A panorama is not limited to horizontal shots only. Vertical images are also an option. How is a Panorama Made? Panoramic photos are created by taking a series of overlapping photos and merging them together using software. Why Not Just Crop a Photo? • Making a panorama by cropping deletes a lot of data from the image. • That’s not a problem if you are just going to view it in a small format or at a low resolution. • However, if you want to print the image in a large format the loss of data will limit the size and quality that can be made. Get a Really Wide Angle Lens? • A wide-angle lens still may not be wide enough to capture the whole scene in a single shot. Sometime you just can’t get back far enough. • Photos taken with a wide-angle lens can exhibit undesirable lens distortion. • Lens cost, an auto focus 14mm f/2.8 lens can set you back $1,800 plus. What Lens to Use? • A standard lens works very well for taking panoramic photos. • You get minimal lens distortion, resulting in more realistic panoramic photos. • Choose a lens or focal length on a zoom lens of between 35mm and 80mm. -
Stereo Panography
STEREO PANOGRAPHY How I make 360 degree stereoscopic photos Thomas K Sharpless Philadelphia, PA [email protected] WHY SPHERICAL PHOTOGRAPHY? ● Omnidirectional view of a place and time ● Very high resolution possible ● Immersive experience possible WHAT IS A SPHERICAL PHOTO? ● A 360 x 180 degree image ● Processed and stored in a flat format such as equirectangular or cube map. ● Viewed piecewise on a screen using panorama player software with interactive pan and zoom. ● When viewed in a virtual reality headset, you feel that you are inside the picture. SPHERICAL IMAGE FORMATS TOP: 360x180 DEGREE EQUIRECTANGULAR MAP BOTTOM:SIX 90x90 DEGREE CUBE FACES VIEW SPHERICAL PHOTOS ON THE WEB The bathroom panorama, on 360Cities.net Are You Asleep In There? -- Ed Wilcox Same room, different artist, on Roundme.com Now And At The Hour Of Our Death -- Ashley Carrega HOW TO MAKE A SPHERICAL PHOTO ● Use a fish-eye or ultra-wide lens ● Rotate the camera around lens pupil while taking enough photos to cover the sphere ● Use stitching software to combine the photos into a seamless spherical image A PRO PANORAMIC CAMERA SONY A7r FULL FRAME MIRRORLESS CAMERA SIGMA 15 MM 160 DEGREE FISH-EYE LENS A COMPACT PANORAMIC CAMERA SONY ALPHA, SAMYANG 8mm/2.8 160 DEG. FISH-EYE PANORAMIC TRIPOD HEAD NODAL NINJA NN6 WITH MULTI-STOP ROTATOR PANORAMA BUILDING SOFTWARE ESSENTIAL ● PTGui pro ($$) or Hugin (free) ● Adobe Photoshop ($$$) or GIMP (free) VERY USEFUL ● Adobe Lightroom ($$) ● Pano2VR pro ($$) ● Image Magick (free) ESSENTIAL FOR 3D ● sView stereo panorama player (free) ● PT3D stereo stitching helper ($) OMNIDIRECTIONAL STEREO Combines two 19th century innovations: panoramic photos + stereoscopic photos Depends on 21st century digital technology Best viewed on a computer-driven stereopticon, that is, a virtual reality headset OMNISTEREO THEORY An omnistereo photo is a stereo pair of slit-scan panoramas. -
Monitoring Photo Fl08
Monitoring with Panoramas and Fixed Photopoints: Monitoring recreational impacts, and assessing habitat change from the office using panoramic and fixed photopoints. Chip Young Trail Specialist Florida Fish and Wildlife Conservation Commission (FWC) Office of Recreation Services Panoramic Photopoint = multiple photographs taken from one specific point, stitched together to form a single image. Fixed Photopoint = single photograph taken at a specific point in a specific direction (bearing). Why use fixed and/or panoramic photopoints for monitoring? !! Shows condition of area at one place and time. !! Shows change over time at a particular place. !! Possible to monitor many areas in a relatively short period of time in the field (to be later assessed from the office). !! Quick and easy. FWC lead management areas with developed recreational opportunities Shows condition of area at one time and place. Shows change over time at a particular place (site condition) FALL 2007 SPRING 2008 Shows change over time at a particular place (inventory). FALL 2007 FALL 2008 Situations where photopoints are utilized as an efficient way to monitor impacts. !! Trailheads !! Points along trail !! Parking lots !! Camping areas !! Wildlife viewing blinds !! Observation towers !! Boardwalks !! Boat ramps/paddling launches !! Picnic areas !! and many other use areas Trailheads SPRING 2008 FALL 2008 Points along trail SPRING 2008 FALL 2008 Parking lots FALL 2007 SPRING 2008 Camping areas FALL 2007 SPRING 2008 Wildlife viewing blinds SPRING 2008 FALL 2008 More wildlife -
Metadefender Core V4.13.1
MetaDefender Core v4.13.1 © 2018 OPSWAT, Inc. All rights reserved. OPSWAT®, MetadefenderTM and the OPSWAT logo are trademarks of OPSWAT, Inc. All other trademarks, trade names, service marks, service names, and images mentioned and/or used herein belong to their respective owners. Table of Contents About This Guide 13 Key Features of Metadefender Core 14 1. Quick Start with Metadefender Core 15 1.1. Installation 15 Operating system invariant initial steps 15 Basic setup 16 1.1.1. Configuration wizard 16 1.2. License Activation 21 1.3. Scan Files with Metadefender Core 21 2. Installing or Upgrading Metadefender Core 22 2.1. Recommended System Requirements 22 System Requirements For Server 22 Browser Requirements for the Metadefender Core Management Console 24 2.2. Installing Metadefender 25 Installation 25 Installation notes 25 2.2.1. Installing Metadefender Core using command line 26 2.2.2. Installing Metadefender Core using the Install Wizard 27 2.3. Upgrading MetaDefender Core 27 Upgrading from MetaDefender Core 3.x 27 Upgrading from MetaDefender Core 4.x 28 2.4. Metadefender Core Licensing 28 2.4.1. Activating Metadefender Licenses 28 2.4.2. Checking Your Metadefender Core License 35 2.5. Performance and Load Estimation 36 What to know before reading the results: Some factors that affect performance 36 How test results are calculated 37 Test Reports 37 Performance Report - Multi-Scanning On Linux 37 Performance Report - Multi-Scanning On Windows 41 2.6. Special installation options 46 Use RAMDISK for the tempdirectory 46 3. Configuring Metadefender Core 50 3.1. Management Console 50 3.2. -
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. -
How to Digitize Objects?
Access IT Training “Digitisation is the conversion of analogue materials into a digital format for use by software, and decisions made at the time of digitisation have a fundamental impact on the manageability, accessibility and viability of the resources created.” MINERVA Technical Guidelines for Digital Cultural Content Creation Programmes Project Planning Preparing for the Digitization Process . The selection of materials for digitization . The physical preparation of materials for digitization . The digitization process Storage and Management of Digital Master Material Metadata, standards and resource discovery Delivery formats Publishing on the Web Re-use and re-purposing Intellectual Property and Copyright How bad it can be? Digitization strategy . How to develop internal digitization strategy? Setting technical requirements How to handle scanned material? Dealing with Digital Master copies Scanning equipment Files are too big . Long download time . File is too big for browser to handle ▪ e.g. huge PDF files Using inappropriate file formats for online delivery . proprietary/closed/not well known file formats may cause problems for users, webcrawlers, screen readers Files are too small . Unreadable content – to low resolution Digital Master material is removed after creation of web delivery formats Lack of text recognition . Even the best metadata is not as useful as properly recognized and indexed text “A digitization project has many dimensions and no two digitization projects are identical. Each project varies according to the type of materials being digitized, the timescale, budget, staff skills and other factors. […] Each project will need to develop a project plan to fit its particular circumstances.” MINERVA Technical Guidelines for Digital Cultural Content Creation Programmes Project digitization strategy should reflect specific (long and short term) goals and objectives Such a document can be created for one institution/project/country What can be inside digitization strategy? What will be digitized? . -
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]. -
Op E N So U R C E Yea R B O O K 2 0
OPEN SOURCE YEARBOOK 2016 ..... ........ .... ... .. .... .. .. ... .. OPENSOURCE.COM Opensource.com publishes stories about creating, adopting, and sharing open source solutions. Visit Opensource.com to learn more about how the open source way is improving technologies, education, business, government, health, law, entertainment, humanitarian efforts, and more. Submit a story idea: https://opensource.com/story Email us: [email protected] Chat with us in Freenode IRC: #opensource.com . OPEN SOURCE YEARBOOK 2016 . OPENSOURCE.COM 3 ...... ........ .. .. .. ... .... AUTOGRAPHS . ... .. .... .. .. ... .. ........ ...... ........ .. .. .. ... .... AUTOGRAPHS . ... .. .... .. .. ... .. ........ OPENSOURCE.COM...... ........ .. .. .. ... .... ........ WRITE FOR US ..... .. .. .. ... .... 7 big reasons to contribute to Opensource.com: Career benefits: “I probably would not have gotten my most recent job if it had not been for my articles on 1 Opensource.com.” Raise awareness: “The platform and publicity that is available through Opensource.com is extremely 2 valuable.” Grow your network: “I met a lot of interesting people after that, boosted my blog stats immediately, and 3 even got some business offers!” Contribute back to open source communities: “Writing for Opensource.com has allowed me to give 4 back to a community of users and developers from whom I have truly benefited for many years.” Receive free, professional editing services: “The team helps me, through feedback, on improving my 5 writing skills.” We’re loveable: “I love the Opensource.com team. I have known some of them for years and they are 6 good people.” 7 Writing for us is easy: “I couldn't have been more pleased with my writing experience.” Email us to learn more or to share your feedback about writing for us: https://opensource.com/story Visit our Participate page to more about joining in the Opensource.com community: https://opensource.com/participate Find our editorial team, moderators, authors, and readers on Freenode IRC at #opensource.com: https://opensource.com/irc . -
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. -
DVD-Ofimática 2014-07
(continuación 2) Calizo 0.2.5 - CamStudio 2.7.316 - CamStudio Codec 1.5 - CDex 1.70 - CDisplayEx 1.9.09 - cdrTools FrontEnd 1.5.2 - Classic Shell 3.6.8 - Clavier+ 10.6.7 - Clementine 1.2.1 - Cobian Backup 8.4.0.202 - Comical 0.8 - ComiX 0.2.1.24 - CoolReader 3.0.56.42 - CubicExplorer 0.95.1 - Daphne 2.03 - Data Crow 3.12.5 - DejaVu Fonts 2.34 - DeltaCopy 1.4 - DVD-Ofimática Deluge 1.3.6 - DeSmuME 0.9.10 - Dia 0.97.2.2 - Diashapes 0.2.2 - digiKam 4.1.0 - Disk Imager 1.4 - DiskCryptor 1.1.836 - Ditto 3.19.24.0 - DjVuLibre 3.5.25.4 - DocFetcher 1.1.11 - DoISO 2.0.0.6 - DOSBox 0.74 - DosZip Commander 3.21 - Double Commander 0.5.10 beta - DrawPile 2014-07 0.9.1 - DVD Flick 1.3.0.7 - DVDStyler 2.7.2 - Eagle Mode 0.85.0 - EasyTAG 2.2.3 - Ekiga 4.0.1 2013.08.20 - Electric Sheep 2.7.b35 - eLibrary 2.5.13 - emesene 2.12.9 2012.09.13 - eMule 0.50.a - Eraser 6.0.10 - eSpeak 1.48.04 - Eudora OSE 1.0 - eViacam 1.7.2 - Exodus 0.10.0.0 - Explore2fs 1.08 beta9 - Ext2Fsd 0.52 - FBReader 0.12.10 - ffDiaporama 2.1 - FileBot 4.1 - FileVerifier++ 0.6.3 DVD-Ofimática es una recopilación de programas libres para Windows - FileZilla 3.8.1 - Firefox 30.0 - FLAC 1.2.1.b - FocusWriter 1.5.1 - Folder Size 2.6 - fre:ac 1.0.21.a dirigidos a la ofimática en general (ofimática, sonido, gráficos y vídeo, - Free Download Manager 3.9.4.1472 - Free Manga Downloader 0.8.2.325 - Free1x2 0.70.2 - Internet y utilidades). -
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 ...........................................................................