• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer

Electrical Engineering News and Products

Electronics Engineering Resources, Articles, Forums, Tear Down Videos and Technical Electronics How-To's

  • Products / Components
    • Analog ICs
    • Connectors
    • Microcontrollers
    • Power Electronics
    • Sensors
    • Test and Measurement
    • Wire / Cable
  • Applications
    • Automotive/Transportation
    • Industrial
    • IoT
    • Medical
    • Telecommunications
    • Wearables
    • Wireless
  • Resources
    • DesignFast
    • Digital Issues
    • Engineering Week
    • Oscilloscope Product Finder
    • Podcasts
    • Webinars / Digital Events
    • White Papers
    • Women in Engineering
  • Videos
    • Teschler’s Teardown Videos
    • EE Videos and Interviews
  • Learning Center
    • EE Classrooms
    • Design Guides
      • WiFi & the IOT Design Guide
      • Microcontrollers Design Guide
      • State of the Art Inductors Design Guide
    • FAQs
    • Ebooks / Tech Tips
  • EE Forums
    • EDABoard.com
    • Electro-Tech-Online.com
  • 5G

Real Or Virtual: Dartmouth Scientists Ask — Can We Tell The Difference?

February 19, 2016 By Dartmouth College

A Dartmouth College-led study shows that people find it increasingly difficult to distinguish between computer-generated images and real photos, but that a small amount of training greatly improves their accuracy.

The findings, which have implications for the legality and prosecution of child pornography, appear in the journal ACM Transactions on Applied Perception. A PDF is available on request.

As 3-D rendering software and hardware become more powerful, the computer-generated characters they create for film making, video games, advertising and other venues have become more photo-realistic. But the drive to create virtual characters that are indistinguishable from human characters has also given rise to complex forensic and legal issues, such as the need to distinguish between computer-generated and photographic images of child pornography, says senior author Hany Farid, a professor of computer science and a pioneering researcher in digital forensics at Dartmouth.

“As computer-generated images quickly become more realistic, it becomes increasingly difficult for untrained human observers to make this distinction between the virtual and the real,” Farid says. “This can be problematic when a photograph is introduced into a court of law and the jury has to assess its authenticity.”

Legal background:

 

  • In 1996, Congress passed the Child Pornography Prevention Act (CPPA), which made illegal “any visual depiction including any photograph, film, video, picture or computer-generated image that is, or appears to be, of a minor engaging in sexually explicit conduct.”

     

  • In 2002, the U.S. Supreme Court ruled that the CPPA infringed on the First Amendment and classified computer-generated child pornography as protected speech. As a result, defense attorneys need only claim their client’s images of child pornography are computer generated.

     

  • In 2003, Congress passed the PROTECT Act, which classified computer generated child pornography as “obscene,” but this law didn’t eliminate the so-called “virtual defense” because juries are reluctant to send a defendant to prison for merely possessing computer-generated imagery when no real child was harmed.

     

In their new study, Farid’s team conducted perceptual experiments in which 60 high-quality computer-generated and photographic images of men’s and women’s faces were shown to 250 observers. Each observer was asked to classify each image as either computer generated or photographic. Observers correctly classified photographic images 92 percent of the time, but correctly classified computer-generated images only 60 percent of the time.

In a follow-up experiment, the researchers found that when a second set of observers was provided some training prior to the experiment, their accuracy on classifying photographic images fell slightly to 85 percent but their accuracy on computer-generated images jumped to 76 percent.

With or without training, observers performed much worse than Farid’s team observed five years ago in a study when computer-generated imagery was not as photo-realistic.

“We expect that as computer-graphics technology continues to advance, observers will find it increasingly difficult to distinguish computer-generated from photographic images,” Farid says. “While this can be considered a success for the computer-graphics community, it will no doubt lead to complications for the legal and forensic communities. We expect that human observers will be able to continue to perform this task for a few years to come, but eventually we will have to refine existing techniques and develop new computational methods that can detect fine-grained image details that may not be identifiable by the human visual system.”

 

DesignFast Banner version: 2cc8ae61

Filed Under: Displays

Primary Sidebar

EE Training Center Classrooms

EE Classrooms

Featured Resources

  • EE World Online Learning Center
  • CUI Devices – CUI Insights Blog
  • EE Classroom: Power Delivery
  • EE Classroom: Building Automation
  • EE Classroom: Aerospace & Defense
  • EE Classroom: Grid Infrastructure
Search Millions of Parts from Thousands of Suppliers.

Search Now!
design fast globle

R&D World Podcasts

R&D 100 Episode 7
See More >

Current Digital Issue

April 2022 Special Edition: Internet of Things Handbook

How to turn off a smart meter the hard way Potential cyber attacks have a lot of people worried thanks to the recent conflict in Ukraine. So it might be appropriate to review what happened when cybersecurity fi rm FireEye’s Mandiant team demonstrated how to infiltrate the network of a North American utility. During this…

Digital Edition Back Issues

Sponsored Content

Positioning in 5G NR – A look at the technology and related test aspects

Radar, NFC, UV Sensors, and Weather Kits are Some of the New RAKwireless Products for IoT

5G Connectors: Enabling the global 5G vision

Control EMI with I-PEX ZenShield™ Connectors

Speed-up time-to-tapeout with the Aprisa digital place-and-route system and Solido Characterization Suite

Siemens Analogue IC Design Simulation Flow

More Sponsored Content >>

RSS Current EDABoard.com discussions

  • Help with Verilog replicate operator
  • ESP Serial Communication Problem with RS232
  • How to mark layer comments in CAP of spef file using StarRC
  • MAX5389 resetting by noise
  • Simulation of resonator in HFSS

RSS Current Electro-Tech-Online.com Discussions

  • Will Header and socket hold this PCB OK?
  • Relaxation oscillator with neon or...
  • software PWM
  • MPlab8 remove page breaks in list file
  • ATOM Diy module

Oscilloscopes Product Finder

Footer

EE World Online

EE WORLD ONLINE NETWORK

  • 5G Technology World
  • Analog IC Tips
  • Battery Power Tips
  • Connector Tips
  • DesignFast
  • EDABoard Forums
  • Electro-Tech-Online Forums
  • Engineer's Garage
  • Microcontroller Tips
  • Power Electronic Tips
  • Sensor Tips
  • Test and Measurement Tips
  • Wire & Cable Tips

EE WORLD ONLINE

  • Subscribe to our newsletter
  • Lee's teardown videos
  • Advertise with us
  • Contact us
  • About Us
Follow us on TwitterAdd us on FacebookConnect with us on LinkedIn Follow us on YouTube Add us on Instagram

Copyright © 2022 · WTWH Media LLC and its licensors. All rights reserved.
The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media.

Privacy Policy