Depth of Field for the Tilted Lens Plane
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Completing a Photography Exhibit Data Tag
Completing a Photography Exhibit Data Tag Current Data Tags are available at: https://unl.box.com/s/1ttnemphrd4szykl5t9xm1ofiezi86js Camera Make & Model: Indicate the brand and model of the camera, such as Google Pixel 2, Nikon Coolpix B500, or Canon EOS Rebel T7. Focus Type: • Fixed Focus means the photographer is not able to adjust the focal point. These cameras tend to have a large depth of field. This might include basic disposable cameras. • Auto Focus means the camera automatically adjusts the optics in the lens to bring the subject into focus. The camera typically selects what to focus on. However, the photographer may also be able to select the focal point using a touch screen for example, but the camera will automatically adjust the lens. This might include digital cameras and mobile device cameras, such as phones and tablets. • Manual Focus allows the photographer to manually adjust and control the lens’ focus by hand, usually by turning the focus ring. Camera Type: Indicate whether the camera is digital or film. (The following Questions are for Unit 2 and 3 exhibitors only.) Did you manually adjust the aperture, shutter speed, or ISO? Indicate whether you adjusted these settings to capture the photo. Note: Regardless of whether or not you adjusted these settings manually, you must still identify the images specific F Stop, Shutter Sped, ISO, and Focal Length settings. “Auto” is not an acceptable answer. Digital cameras automatically record this information for each photo captured. This information, referred to as Metadata, is attached to the image file and goes with it when the image is downloaded to a computer for example. -
Optics – Panoramic Lens Applications Revisited
Panoramic Lens Applications Revisited Simon Thibault* M.Sc., Ph.D., Eng Director, Optics Division/Principal Optical Designer ImmerVision 2020 University, Montreal, Quebec, H3A 2A5 Canada ABSTRACT During the last few years, innovative optical design strategies to generate and control image mapping have been successful in producing high-resolution digital imagers and projectors. This new generation of panoramic lenses includes catadioptric panoramic lenses, panoramic annular lenses, visible/IR fisheye lenses, anamorphic wide-angle attachments, and visible/IR panomorph lenses. Given that a wide-angle lens images a large field of view on a limited number of pixels, a systematic pixel-to-angle mapping will help the efficient use of each pixel in the field of view. In this paper, we present several modern applications of these modern types of hemispheric lenses. Recently, surveillance and security applications have been proposed and published in Security and Defence symposium. However, modern hemispheric lens can be used in many other fields. A panoramic imaging sensor contributes most to the perception of the world. Panoramic lenses are now ready to be deployed in many optical solutions. Covered applications include, but are not limited to medical imaging (endoscope, rigiscope, fiberscope…), remote sensing (pipe inspection, crime scene investigation, archeology…), multimedia (hemispheric projector, panoramic image…). Modern panoramic technologies allow simple and efficient digital image processing and the use of standard image analysis features (motion estimation, segmentation, object tracking, pattern recognition) in the complete 360o hemispheric area. Keywords: medical imaging, image analysis, immersion, omnidirectional, panoramic, panomorph, multimedia, total situation awareness, remote sensing, wide-angle 1. INTRODUCTION Photography was invented by Daguerre in 1837, and at that time the main photographic objective was that the lens should cover a wide-angle field of view with a relatively high aperture1. -
Visual Tilt Estimation for Planar-Motion Methods in Indoor Mobile Robots
robotics Article Visual Tilt Estimation for Planar-Motion Methods in Indoor Mobile Robots David Fleer Computer Engineering Group, Faculty of Technology, Bielefeld University, D-33594 Bielefeld, Germany; dfl[email protected]; Tel.: +49-521-106-5279 Received: 22 September 2017; Accepted: 28 October 2017; Published: date Abstract: Visual methods have many applications in mobile robotics problems, such as localization, navigation, and mapping. Some methods require that the robot moves in a plane without tilting. This planar-motion assumption simplifies the problem, and can lead to improved results. However, tilting the robot violates this assumption, and may cause planar-motion methods to fail. Such a tilt should therefore be corrected. In this work, we estimate a robot’s tilt relative to a ground plane from individual panoramic images. This estimate is based on the vanishing point of vertical elements, which commonly occur in indoor environments. We test the quality of two methods on images from several environments: An image-space method exploits several approximations to detect the vanishing point in a panoramic fisheye image. The vector-consensus method uses a calibrated camera model to solve the tilt-estimation problem in 3D space. In addition, we measure the time required on desktop and embedded systems. We previously studied visual pose-estimation for a domestic robot, including the effect of tilts. We use these earlier results to establish meaningful standards for the estimation error and time. Overall, we find the methods to be accurate and fast enough for real-time use on embedded systems. However, the tilt-estimation error increases markedly in environments containing relatively few vertical edges. -
Depth-Aware Blending of Smoothed Images for Bokeh Effect Generation
1 Depth-aware Blending of Smoothed Images for Bokeh Effect Generation Saikat Duttaa,∗∗ aIndian Institute of Technology Madras, Chennai, PIN-600036, India ABSTRACT Bokeh effect is used in photography to capture images where the closer objects look sharp and every- thing else stays out-of-focus. Bokeh photos are generally captured using Single Lens Reflex cameras using shallow depth-of-field. Most of the modern smartphones can take bokeh images by leveraging dual rear cameras or a good auto-focus hardware. However, for smartphones with single-rear camera without a good auto-focus hardware, we have to rely on software to generate bokeh images. This kind of system is also useful to generate bokeh effect in already captured images. In this paper, an end-to-end deep learning framework is proposed to generate high-quality bokeh effect from images. The original image and different versions of smoothed images are blended to generate Bokeh effect with the help of a monocular depth estimation network. The proposed approach is compared against a saliency detection based baseline and a number of approaches proposed in AIM 2019 Challenge on Bokeh Effect Synthesis. Extensive experiments are shown in order to understand different parts of the proposed algorithm. The network is lightweight and can process an HD image in 0.03 seconds. This approach ranked second in AIM 2019 Bokeh effect challenge-Perceptual Track. 1. Introduction tant problem in Computer Vision and has gained attention re- cently. Most of the existing approaches(Shen et al., 2016; Wad- Depth-of-field effect or Bokeh effect is often used in photog- hwa et al., 2018; Xu et al., 2018) work on human portraits by raphy to generate aesthetic pictures. -
DEPTH of FIELD CHEAT SHEET What Is Depth of Field? the Depth of Field (DOF) Is the Area of a Scene That Appears Sharp in the Image
Ms. Brown Photography One DEPTH OF FIELD CHEAT SHEET What is Depth of Field? The depth of field (DOF) is the area of a scene that appears sharp in the image. DOF refers to the zone of focus in a photograph or the distance between the closest and furthest parts of the picture that are reasonably sharp. Depth of field is determined by three main attributes: 1) The APERTURE (size of the opening) 2) The SHUTTER SPEED (time of the exposure) 3) DISTANCE from the subject being photographed 4) SHALLOW and GREAT Depth of Field Explained Shallow Depth of Field: In shallow depth of field, the main subject is emphasized by making all other elements out of focus. (Foreground or background is purposely blurry) Aperture: The larger the aperture, the shallower the depth of field. Distance: The closer you are to the subject matter, the shallower the depth of field. ***You cannot achieve shallow depth of field with excessive bright light. This means no bright sunlight pictures for shallow depth of field because you can’t open the aperture wide enough in bright light.*** SHALLOW DOF STEPS: 1. Set your camera to a small f/stop number such as f/2-f/5.6. 2. GET CLOSE to your subject (between 2-5 feet away). 3. Don’t put the subject too close to its background; the farther away the subject is from its background the better. 4. Set your camera for the correct exposure by adjusting only the shutter speed (aperture is already set). 5. Find the best composition, focus the lens of your camera and take your picture. -
Video Tripod Head
thank you for choosing magnus. One (1) year limited warranty Congratulations on your purchase of the VPH-20 This MAGNUS product is warranted to the original purchaser Video Pan Head by Magnus. to be free from defects in materials and workmanship All Magnus Video Heads are designed to balance under normal consumer use for a period of one (1) year features professionals want with the affordability they from the original purchase date or thirty (30) days after need. They’re durable enough to provide many years replacement, whichever occurs later. The warranty provider’s of trouble-free service and enjoyment. Please carefully responsibility with respect to this limited warranty shall be read these instructions before setting up and using limited solely to repair or replacement, at the provider’s your Video Pan Head. discretion, of any product that fails during normal use of this product in its intended manner and in its intended VPH-20 Box Contents environment. Inoperability of the product or part(s) shall be determined by the warranty provider. If the product has • VPH-20 Video Pan Head Owner’s been discontinued, the warranty provider reserves the right • 3/8” and ¼”-20 reducing bushing to replace it with a model of equivalent quality and function. manual This warranty does not cover damage or defect caused by misuse, • Quick-release plate neglect, accident, alteration, abuse, improper installation or maintenance. EXCEPT AS PROVIDED HEREIN, THE WARRANTY Key Features PROVIDER MAKES NEITHER ANY EXPRESS WARRANTIES NOR ANY IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED Tilt-Tension Adjustment Knob TO ANY IMPLIED WARRANTY OF MERCHANTABILITY Tilt Lock OR FITNESS FOR A PARTICULAR PURPOSE. -
Camera System Considerations for Geomorphic Applications of Sfm Photogrammetry Adam R
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln USGS Staff -- ubP lished Research US Geological Survey 2017 Camera system considerations for geomorphic applications of SfM photogrammetry Adam R. Mosbrucker US Geological Survey, [email protected] Jon J. Major US Geological Survey Kurt R. Spicer US Geological Survey John Pitlick University of Colorado Follow this and additional works at: http://digitalcommons.unl.edu/usgsstaffpub Part of the Geology Commons, Oceanography and Atmospheric Sciences and Meteorology Commons, Other Earth Sciences Commons, and the Other Environmental Sciences Commons Mosbrucker, Adam R.; Major, Jon J.; Spicer, Kurt R.; and Pitlick, John, "Camera system considerations for geomorphic applications of SfM photogrammetry" (2017). USGS Staff -- Published Research. 1007. http://digitalcommons.unl.edu/usgsstaffpub/1007 This Article is brought to you for free and open access by the US Geological Survey at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in USGS Staff -- ubP lished Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. EARTH SURFACE PROCESSES AND LANDFORMS Earth Surf. Process. Landforms 42, 969–986 (2017) Published 2016. This article is a U.S. Government work and is in the public domain in the USA Published online 3 January 2017 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/esp.4066 Camera system considerations for geomorphic applications of SfM photogrammetry Adam R. Mosbrucker,1* Jon J. Major,1 Kurt R. Spicer1 and John Pitlick2 1 US Geological Survey, Vancouver, WA USA 2 Geography Department, University of Colorado, Boulder, CO USA Received 17 October 2014; Revised 11 October 2016; Accepted 12 October 2016 *Correspondence to: Adam R. -
Colour Relationships Using Traditional, Analogue and Digital Technology
Colour Relationships Using Traditional, Analogue and Digital Technology Peter Burke Skills Victoria (TAFE)/Italy (Veneto) ISS Institute Fellowship Fellowship funded by Skills Victoria, Department of Innovation, Industry and Regional Development, Victorian Government ISS Institute Inc MAY 2011 © ISS Institute T 03 9347 4583 Level 1 F 03 9348 1474 189 Faraday Street [email protected] Carlton Vic E AUSTRALIA 3053 W www.issinstitute.org.au Published by International Specialised Skills Institute, Melbourne Extract published on www.issinstitute.org.au © Copyright ISS Institute May 2011 This publication is copyright. No part may be reproduced by any process except in accordance with the provisions of the Copyright Act 1968. Whilst this report has been accepted by ISS Institute, ISS Institute cannot provide expert peer review of the report, and except as may be required by law no responsibility can be accepted by ISS Institute for the content of the report or any links therein, or omissions, typographical, print or photographic errors, or inaccuracies that may occur after publication or otherwise. ISS Institute do not accept responsibility for the consequences of any action taken or omitted to be taken by any person as a consequence of anything contained in, or omitted from, this report. Executive Summary This Fellowship study explored the use of analogue and digital technologies to create colour surfaces and sound experiences. The research focused on art and design activities that combine traditional analogue techniques (such as drawing or painting) with print and electronic media (from simple LED lighting to large-scale video projections on buildings). The Fellow’s rich and varied self-directed research was centred in Venice, Italy, with visits to France, Sweden, Scotland and the Netherlands to attend large public events such as the Biennale de Venezia and the Edinburgh Festival, and more intimate moments where one-on-one interviews were conducted with renown artists in their studios. -
Depth of Field PDF Only
Depth of Field for Digital Images Robin D. Myers Better Light, Inc. In the days before digital images, before the advent of roll film, photography was accomplished with photosensitive emulsions spread on glass plates. After processing and drying the glass negative, it was contact printed onto photosensitive paper to produce the final print. The size of the final print was the same size as the negative. During this period some of the foundational work into the science of photography was performed. One of the concepts developed was the circle of confusion. Contact prints are usually small enough that they are normally viewed at a distance of approximately 250 millimeters (about 10 inches). At this distance the human eye can resolve a detail that occupies an angle of about 1 arc minute. The eye cannot see a difference between a blurred circle and a sharp edged circle that just fills this small angle at this viewing distance. The diameter of this circle is called the circle of confusion. Converting the diameter of this circle into a size measurement, we get about 0.1 millimeters. If we assume a standard print size of 8 by 10 inches (about 200 mm by 250 mm) and divide this by the circle of confusion then an 8x10 print would represent about 2000x2500 smallest discernible points. If these points are equated to their equivalence in digital pixels, then the resolution of a 8x10 print would be about 2000x2500 pixels or about 250 pixels per inch (100 pixels per centimeter). The circle of confusion used for 4x5 film has traditionally been that of a contact print viewed at the standard 250 mm viewing distance. -
Dof 4.0 – a Depth of Field Calculator
DoF 4.0 – A Depth of Field Calculator Last updated: 8-Mar-2021 Introduction When you focus a camera lens at some distance and take a photograph, the further subjects are from the focus point, the blurrier they look. Depth of field is the range of subject distances that are acceptably sharp. It varies with aperture and focal length, distance at which the lens is focused, and the circle of confusion – a measure of how much blurring is acceptable in a sharp image. The tricky part is defining what acceptable means. Sharpness is not an inherent quality as it depends heavily on the magnification at which an image is viewed. When viewed from the same distance, a smaller version of the same image will look sharper than a larger one. Similarly, an image that looks sharp as a 4x6" print may look decidedly less so at 16x20". All other things being equal, the range of in-focus distances increases with shorter lens focal lengths, smaller apertures, the farther away you focus, and the larger the circle of confusion. Conversely, longer lenses, wider apertures, closer focus, and a smaller circle of confusion make for a narrower depth of field. Sometimes focus blur is undesirable, and sometimes it’s an intentional creative choice. Either way, you need to understand depth of field to achieve predictable results. What is DoF? DoF is an advanced depth of field calculator available for both Windows and Android. What DoF Does Even if your camera has a depth of field preview button, the viewfinder image is just too small to judge critical sharpness. -
Surface Tilt (The Direction of Slant): a Neglected Psychophysical Variable
Perception & Psychophysics 1983,33 (3),241-250 Surface tilt (the direction of slant): A neglected psychophysical variable KENT A. STEVENS Massachusetts InstituteofTechnology, Cambridge, Massachusetts Surface slant (the angle between the line of sight and the surface normal) is an important psy chophysical variable. However, slant angle captures only one of the two degrees of freedom of surface orientation, the other being the direction of slant. Slant direction, measured in the image plane, coincides with the direction of the gradient of distance from viewer to surface and, equivalently, with the direction the surface normal would point if projected onto the image plane. Since slant direction may be quantified by the tilt of the projected normal (which ranges over 360 deg in the frontal plane), it is referred to here as surfacetilt. (Note that slant angle is mea sured perpendicular to the image plane, whereas tilt angle is measured in the image plane.) Com pared with slant angle's popularity as a psychophysical variable, the attention paid to surface tilt seems undeservedly scant. Experiments that demonstrate a technique for measuring ap parent surface tilt are reported. The experimental stimuli were oblique crosses and parallelo grams, which suggest oriented planes in SoD. The apparent tilt of the plane might beprobed by orienting a needle in SoD so as to appear normal, projecting the normal onto the image plane, and measuring its direction (e.g., relative to the horizontal). It is shown to be preferable, how ever, to merely rotate a line segment in 2-D, superimposed on the display, until it appears nor mal to the perceived surface. -
Rethinking Coalitions: Anti-Pornography Feminists, Conservatives, and Relationships Between Collaborative Adversarial Movements
Rethinking Coalitions: Anti-Pornography Feminists, Conservatives, and Relationships between Collaborative Adversarial Movements Nancy Whittier This research was partially supported by the Center for Advanced Study in Behavioral Sciences. The author thanks the following people for their comments: Martha Ackelsberg, Steven Boutcher, Kai Heidemann, Holly McCammon, Ziad Munson, Jo Reger, Marc Steinberg, Kim Voss, the anonymous reviewers for Social Problems, and editor Becky Pettit. A previous version of this paper was presented at the 2011 Annual Meetings of the American Sociological Association. Direct correspondence to Nancy Whittier, 10 Prospect St., Smith College, Northampton MA 01063. Email: [email protected]. 1 Abstract Social movements interact in a wide range of ways, yet we have only a few concepts for thinking about these interactions: coalition, spillover, and opposition. Many social movements interact with each other as neither coalition partners nor opposing movements. In this paper, I argue that we need to think more broadly and precisely about the relationships between movements and suggest a framework for conceptualizing non- coalitional interaction between movements. Although social movements scholars have not theorized such interactions, “strange bedfellows” are not uncommon. They differ from coalitions in form, dynamics, relationship to larger movements, and consequences. I first distinguish types of relationships between movements based on extent of interaction and ideological congruence and describe the relationship between collaborating, ideologically-opposed movements, which I call “collaborative adversarial relationships.” Second, I differentiate among the dimensions along which social movements may interact and outline the range of forms that collaborative adversarial relationships may take. Third, I theorize factors that influence collaborative adversarial relationships’ development over time, the effects on participants and consequences for larger movements, in contrast to coalitions.