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You are viewing : > Home > Research > Research Profiles > Dezombify
  • Computational Analysis of Ice Hockey Gameplay
  • Online Music Recommendation and the Problem of Missing Ratings
  • Speech Summarization
  • Novel Interfaces for Molecular Visualization
  • Using a Physical Object to Control a Virtual 3D Object
  • Amigo: Proximity-Based Authentication
  • Grapevine
  • Modelling Complex Financial Instruments
  • Using Language to Learn Structure Appearance Models for Image Annotation
  • Stylization of Character Motion
  • ILoveSketch
  • JSCOOP: A High-Level Concurrency Framework for Java
  • Dezombify
  • SPIDER Data Cleaning Tool
  • Cognitive Orthosis for Assisting Activities in the Home
  • NAViGaTOR Visualizing Protein Interaction Networks
  • Friend Forecaster: Cellphone Software Aiding Memory for Games

Dezombify

DezombifyMixed lighting is a problem faced by photographers everywhere.  Yellowish incandescent light make people look like they have jaundice.  Harsh blue light from camera flashes make people appear pale like zombies.  Through chromatic adaptation, human perception allows us to see the true skin tones of people regardless of the light colour illuminating the scene.  Virtually all digital cameras lack this corrective process.

"Dezombify" is a semi-automated process for applying digital chromatic adaptation to large photo collections.  It uses face detection to identify skin tones and recolours photographs so people appear less like the undead.

More project information can be found here.

Jason Montojo Graduate Student
Greg Wilson Faculty

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Computer Science

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