Study Shows Restricting Field of View Alleviates VR Sickness

For some users, virtual reality creates motion sickness, with the result that they either avoid VR completely or limit their time with VR experiences. Now, two engineering professors at Columbia University say that they’ve come up with a solution to VR sickness that can be easily applied to the current array of consumer VR headsets, including Oculus Rift, HTC Vive, Sony PlayStation VR and Google Cardboard. The solution is simply a matter of dynamically changing — sometimes quite subtly — the field of view (FOV). Continue reading Study Shows Restricting Field of View Alleviates VR Sickness

Dropbox Hires Computer Vision Experts to Mine Photographs

Dropbox wants to add image recognition software to its cloud storage service so that photos would automatically be tagged with the objects, people, and places found in the images. The company has hired the co-founders of Kriegman-Belhumeur Vision Technology, Peter Belhumeur and David Kriegman, to engineer the new technology. The two men are university professors with extensive experience in computer vision, facial recognition, and machine learning. Continue reading Dropbox Hires Computer Vision Experts to Mine Photographs

Transparency for the Web: XRay Tracks Use of Personal Data

In a step toward protecting the personal data of online users, researchers at Columbia University have created new software called XRay that can observe and predict how tech companies are using the personal data that they collect. The software is based on research related to Google’s Gmail ads, Amazon recommendations, and YouTube recommendations. XRay, which will help privacy-concerned watchdogs track how personal data is used, is still in development. Continue reading Transparency for the Web: XRay Tracks Use of Personal Data

Next-Gen Music Retrieval: Free Million-Song Dataset Released by Echo Nest

  • The Million Song Dataset has been released for free by The Echo Nest music application company to facilitate research into music recommendation engines. The dataset consists of audio features and metadata (but not the actual music) for a million popular music tracks.
  • Ars Technica reports that the dataset is a “freely-available collection of audio features and metadata for a million contemporary popular music tracks,” being analyzed by Columbia University’s Laboratory for the Recognition and Organization of Speech and Audio.
  • Currently, services like Pandora make use of musicologists to catalog the characteristics of songs. Researchers are looking at methods for computers to analyze songs in order to make recommendations based on your preferences. The dataset could potentially be used to develop a new generation of Music Information Retrieval services.
  • The National Science Foundation is also conducting The Listening Machine Project which is focused on analyzing “the individual sources present in a real-world sound recording,” which could lead to improved perception for robots, new prosthetic devices for hearing impaired and “a wide range of novel applications in content-based multimedia indexing,” explained LMP’s Dan Ellis, associate professor of Electrical Engineering at Columbia.

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