camera basics
play

CAMERA BASICS 353#01&&&&&slide&0& - PowerPoint PPT Presentation

Aug 18, 2022 •167 likes •254 views

CAMERA BASICS 353#01&&&&&slide&0& Contact Information Jamie Companeschi (com pan es k ) 337F office: B08 phone: 617.353.6348 email: jamie@bu.edu web:blogs.bu.edu/jamie

  1. CAMERA BASICS 353#01&&&&&slide&0&

  2. Contact Information Jamie Companeschi (com · pan · es · k ē ) 337F office: B08 phone: 617.353.6348 email: jamie@bu.edu web:blogs.bu.edu/jamie 353#01&&&&&slide&1&

  3. Key Notes · operate camera and expose a still image · understand and control aperture · F-stop scale · understand and control focus 353#01&&&&&slide&2&

  4. Media Storage SDHC – HD video recording SD – audio recording · class 6* (20MB/sec.) · 2GB · 4GB (12min. HD record time) Drive – external hard drive · 7200 RPM · FireWire 800** Shop price/brand drive https://secure.bhphotovideo.com/bnh/controller/home?O=wishListDetail_NEW.jsp&A=wishlistDetail&Q=&li=7C08D4EB9D card https://secure.bhphotovideo.com/bnh/controller/home?O=wishListDetail_NEW.jsp&A=wishlistDetail&Q=&li=73996BC5DB * recommend class 10 ** COM Labs set up for firewire 800 and select USB3 (blue connector) 353#01&&&&&slide&3&

  5. F-stop Scale F-stop : conceptual foundation of exposure Aperture : opening in LENS that allows light through · created by iris blades/leafs · measured in F-stops* F 1.4 F 2 F 2.8 F 4 F 5.6 F 8 F 11 F 16 F 22 * F-stop is calculation (ratio) of lens allowing light through T-stop is measured (taking into account of transmittance) of light passing through lens 353#01&&&&&slide&4&

  6. Field of View Field of View (F.O.V.) : perceived frame size 16mm& & Focal Length : lens to sensor convergence distance & & & · “lens size” measured in millimeters & & Sensor : digital image acquisition size “footprint” & T2i &(7D)& Gate : film exposure size “footprint” & & Normal : cinematic perception of human eyesight & & & T2i&&&&–&&&&50mm&lens& & 35mm& & & & 35mm&–&50mm&lens& 5D& & & & 5D&&&&&–&&&&50mm&lens & & & Digital&Cine& 353#01&&&&&slide&5&

  7. Camera Setup 1. battery 2. SDHC 3. power 4. Manual 353#01&&&&&slide&6&

  8. Technical Terms DSLR : digital single lens reflex shutter : 1/50 shutter speed aperture : opening created in lens allowing light to pass F-stop scale : 1.4 2 2.8 4 5.6 8 11 16 22 ISO : sensor light sensitivity Color Temp. (WB) : daylight 5600° K tungsten 3200° K Focal Length : lens size (distance of image convergence) Field of View (FOV) : viewable frame size Normal Lens : cinematic perception of human FOV 353#01&&&&&slide&7&

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Basics of Off-Camera Flash Off-Camera Flash www.jedi.com * What is it & why do we use it? *

Basics of Off-Camera Flash Off-Camera Flash www.jedi.com * What is it & why do we use it? *

Basics of Off-Camera Flash Off-Camera Flash www.jedi.com * What is it & why do we use it? * Bouncing on-camera flash to emulate off-camera light * True off-camera flash * Basic examples * Trigger mechanisms * Controlling the amount of

144 views • 11 slides
# Camera camera = Camera.open(); Camera camera

# Camera camera = Camera.open(); Camera camera

# Camera camera = Camera.open(); Camera camera = Camera.open(); camera.setDisplayOrientation(90); camera.setDisplayOrientation(90); camera.unlock(); SurfaceHolder holder = getHolder();

1.34k views • 45 slides
Ray Tracing Basics I Computer Graphics as Virtual Photography real camera photo Photographic

Ray Tracing Basics I Computer Graphics as Virtual Photography real camera photo Photographic

Ray Tracing Basics I Computer Graphics as Virtual Photography real camera photo Photographic Photography: scene (captures processing print light) processing camera Computer 3D synthetic tone model Graphics: models image

441 views • 26 slides
# Camera camera = Camera.open();

# Camera camera = Camera.open();

# Camera camera = Camera.open(); Camera camera = Camera.open(); camera.setDisplayOrientation(90); camera.setDisplayOrientation(90); camera.unlock(); SurfaceHolder holder =

819 views • 33 slides
1 Radiosity - Basics Radiosity - Basics Based on thermal engineering models for Ray

1 Radiosity - Basics Radiosity - Basics Based on thermal engineering models for Ray

Computer Graphics as Virtual Photography real camera photo Photographic Photography: scene (captures processing print Radiosity light) processing camera Computer 3D synthetic tone model Graphics: models image reproduction

327 views • 10 slides
Camera Rongkai Guo Why Camera First? Games have their own visual rules Contrary to other

Camera Rongkai Guo Why Camera First? Games have their own visual rules Contrary to other

Camera Rongkai Guo Why Camera First? Games have their own visual rules Contrary to other kinds of camera Difficult and Expensive to change a poorly designed camera Rules are needed to govern the camera through the whole game

341 views • 10 slides
Other Camera Controls The LookAt function is only for positioning camera Other ways to

Other Camera Controls The LookAt function is only for positioning camera Other ways to

Other Camera Controls The LookAt function is only for positioning camera Other ways to specify camera position/movement Yaw, pitch, roll Elevation, azimuth, twist Direction angles Flexible Camera Control Sometimes, we want

941 views • 29 slides
Other Camera Controls The LookAt function is only for positioning camera Other ways to

Other Camera Controls The LookAt function is only for positioning camera Other ways to

Other Camera Controls The LookAt function is only for positioning camera Other ways to specify camera position/movement Yaw, pitch, roll Elevation, azimuth, twist Direction angles Flexible Camera Control Sometimes, we

717 views • 26 slides
This Week ! Exposure ! The Art, Science and Algorithms Camera Basics ! Simple Math !

This Week ! Exposure ! The Art, Science and Algorithms Camera Basics ! Simple Math !

This Week ! Exposure ! The Art, Science and Algorithms Camera Basics ! Simple Math ! of Photography ! Zone System ! Exposure & Metering ! CSCI 4900/6900 ! Maria Hybinette ! 1 ! 2 ! Maria Hybinette ! Exposure ! Shutter Speed !

324 views • 5 slides
holder.addCallback(this); holder.setType(SurfaceHolder.STP); MediaRecorder r = new

holder.addCallback(this); holder.setType(SurfaceHolder.STP); MediaRecorder r = new

Camera camera = Camera.open(); Camera camera = Camera.open(); camera.setDisplayOrientation(90); camera.setDisplayOrientation(90); camera.unlock(); SurfaceHolder holder = getHolder(); holder.addCallback(this);

324 views • 21 slides
C OMPUTATIONAL A SPECTS OF D IGITAL P HOTOGRAPHY P HOTOGRAPHY Image Formation & Camera Basics

C OMPUTATIONAL A SPECTS OF D IGITAL P HOTOGRAPHY P HOTOGRAPHY Image Formation & Camera Basics

CS 89.15/189.5, Fall 2015 C OMPUTATIONAL C OMPUTATIONAL A SPECTS OF D IGITAL P HOTOGRAPHY P HOTOGRAPHY Image Formation & Camera Basics (continued) Wojciech Jarosz wojciech.k.jarosz@dartmouth.edu Agenda Pinhole optics (Simplified) Lenses

1.04k views • 65 slides
Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera

Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera

Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera projects 3D world points onto the 2D image plane Calibration : Find the internal quantities of the camera that affect this process Image center

908 views • 45 slides
Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera

Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera

Humanoid Robotics Camera Parameters Maren Bennewitz What is Camera Calibration? A camera projects 3D world points onto the 2D image plane Calibration : Find the internal quantities of the camera that affect this process Image

527 views • 48 slides
Multi-view geometry Slides from L. Lazebnik Structure from motion Camera 1 Camera 3 Camera 2 R

Multi-view geometry Slides from L. Lazebnik Structure from motion Camera 1 Camera 3 Camera 2 R

Multi-view geometry Slides from L. Lazebnik Structure from motion Camera 1 Camera 3 Camera 2 R 1 ,t 1 R 3 ,t 3 R 2 ,t 2 Figure credit: Noah Snavely Structure from motion ? Camera 1 Camera 3 Camera 2 R 1 ,t 1 R 3 ,t 3 R 2 ,t 2

526 views • 40 slides
Camera and Scene Setup Where to put the camera? How much to show within the frame? When to move

Camera and Scene Setup Where to put the camera? How much to show within the frame? When to move

Camera and Scene Setup Where to put the camera? How much to show within the frame? When to move the camera? Camera Position Catch the most expressive aspect No unintentional surprises How much to show? long shot medium shot closeups

506 views • 15 slides
This Week Exposure (today) The Art, Science and Algorithms Camera Basics Simple Math

This Week Exposure (today) The Art, Science and Algorithms Camera Basics Simple Math

This Week Exposure (today) The Art, Science and Algorithms Camera Basics Simple Math of Photography Metering Zone System Exposure & Metering Maria Hybinette 1 2 Maria Hybinette Exposure Shutter Speed Controls how long

366 views • 7 slides
INTRODUCTION CHRIS WOOD CREATIVE WAYS TAEKWONDO - MILTON KEYNES 10 YEAR ANNIVERSARY IN JUNE 2020

INTRODUCTION CHRIS WOOD CREATIVE WAYS TAEKWONDO - MILTON KEYNES 10 YEAR ANNIVERSARY IN JUNE 2020

INTRODUCTION CHRIS WOOD CREATIVE WAYS TAEKWONDO - MILTON KEYNES 10 YEAR ANNIVERSARY IN JUNE 2020 95 CURRENT MEMBERS - 54% VIRTUAL ATTENDANCE SO FAR PART TIME CLUB - 3 COACHES, BEFORE RESTRICTIONS WERE IMPOSED & WE TAUGHT 11.5 HOURS A WEEK

481 views • 9 slides
CS 4495 Computer Vision Camera Model Aaron Bobick School of Interactive Computing Camera Model

CS 4495 Computer Vision Camera Model Aaron Bobick School of Interactive Computing Camera Model

Camera Model CS 4495 Computer Vision A. Bobick CS 4495 Computer Vision Camera Model Aaron Bobick School of Interactive Computing Camera Model CS 4495 Computer Vision A. Bobick Administrivia Problem set 1: How did it go?

1.16k views • 60 slides
Chiaki Hikage (KMI) References Impacts of satellite galaxies in measuring the redshift

Chiaki Hikage (KMI) References Impacts of satellite galaxies in measuring the redshift

Unveiling cosmic structure formation with galaxy imaging and redshift surveys Chiaki Hikage (KMI) References Impacts of satellite galaxies in measuring the redshift distortions C. Hikage, K. Yamamoto J. Cosmol. Astropart. Phys., 8

574 views • 34 slides
On The Origin Of The Highest Redshift GRBs: GRB 080913 and GRB 090423 Chris Belczynski 1 , 2 1 Los

On The Origin Of The Highest Redshift GRBs: GRB 080913 and GRB 090423 Chris Belczynski 1 , 2 1 Los

Introduction Simulations Conclusions On The Origin Of The Highest Redshift GRBs: GRB 080913 and GRB 090423 Chris Belczynski 1 , 2 1 Los Alamos National Laboratory 2 Astronomical Observatory, Warsaw University and Daniel Holz, Chris Fryer, Edo

539 views • 7 slides
Agents and Environments Berlin Chen 2004 Reference: 1. S. Russell and P. Norvig. Artificial

Agents and Environments Berlin Chen 2004 Reference: 1. S. Russell and P. Norvig. Artificial

Agents and Environments Berlin Chen 2004 Reference: 1. S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach . Chapter 2 AI 2004 Berlin Chen 1 What is an Agent An agent interacts with its environments Perceive

361 views • 33 slides
Lecture on spectroscopy and applications (Brno 9.02.17) Stephane Vennes Astronomical Institute

Lecture on spectroscopy and applications (Brno 9.02.17) Stephane Vennes Astronomical Institute

Lecture on spectroscopy and applications (Brno 9.02.17) Stephane Vennes Astronomical Institute Czech Academy of Sciences Spectroscopy and applications 1 9/02/2017 Syllabus: Physical description: Atoms and molecules; light

1.21k views • 91 slides
Retrieval-augmented language models CS 685, Fall 2020 Advanced Natural Language Processing Mohit

Retrieval-augmented language models CS 685, Fall 2020 Advanced Natural Language Processing Mohit

Retrieval-augmented language models CS 685, Fall 2020 Advanced Natural Language Processing Mohit Iyyer College of Information and Computer Sciences University of Massachusetts Amherst barbershop: 54% BERT barber: 20% Bob went to the

958 views • 38 slides
YJTI at the NTCIR-13 STC Japanese Subtask Dec. 7, 2017 Toru Shimizu 1 Overview

YJTI at the NTCIR-13 STC Japanese Subtask Dec. 7, 2017 Toru Shimizu 1 Overview

YJTI at the NTCIR-13 STC Japanese Subtask Dec. 7, 2017 Toru Shimizu 1 Overview 2 Retrieval or Generation Retrieval-based system Effective if you have a good matching model and enough

410 views • 24 slides

More recommend