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May 31 2012

Using Python for Computer Vision

Python is a tremendous asset when you're trying to classify images, track changes in scenes, search for items within images, implement augmented reality, or do the myriad other things that fall under the umbrella of Computer Vision. In this interview, Jan Erik Solem, author of the upcoming book "Programming Computer Vision with Python," describes the uses for some common operations, and choices programmers have.

Highlights from the full video interview include:

  • The value of Python in computer vision [Discussed at the 0:24 mark]
  • Searching for images within images [Discussed at the 2:13 mark]
  • Clustering or grouping images [Discussed at the 3:22 mark]
  • Constructing a 3D scene from images [Discussed at the 6:11 mark]
  • Modeling and calibrating a camera [Discussed at the 7:22 mark]

You can view the entire conversation in the following video:

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May 29 2012

Four short links: 29 May 2012

  1. South Korean Kinect+RFID Augmented Reality Theme Park -- Sixty-five attractions over seven thematic stages contribute to the experience, which uses 3D video, holograms and augmented reality to immerse guests. As visitors and their avatars move through the park, they interact with the attractions using RFID wristbands, while Kinect sensors recognize their gestures, voices and faces. (via Seb Chan)
  2. Digital Citizenship -- computers in schools should be about more than teaching more than just typing to kids, they should know how to intelligently surf, to assess the quality of their sources, to stay safe from scammers and bullies, to have all the training they need to be citizens in an age when life is increasingly lived online. (via Pia Waugh)
  3. Simulating Anatomically Accurate Facial Expressions (University of Auckland) -- video of a talk demonstrating biomechanical models which permit anatomically accurate facial models.
  4. Depixelizing Pixel Art (Microsoft Research) -- this is totally awesome: turning pixel images into vector drawings, which of course can be smoothly scaled. (via Bruce Sterling)

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