Visage Technologies
Face Tracking & Analysis


April 6, 2016

I like to move it: model for causal motion segmentation

The human ability to detect and segment moving objects works great in every case. We can observe walking stick bugs, since the insect is immediately visible when it starts moving. However, computers usually have problems with multiple objects, complex background geometry, motion of the observer, and even camouflage. People also detect motion instantaneously. There has […]

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Real-time Face Capture and Reenactment of RGB Videos

March 21, 2016

Face2Face: live video editing of facial expressions

  “It’s photoshopped!” is a line that is often heard regarding retouched images. However, nobody still expects to say the same about a video, since the editing of multiple frame requires not only a lot of time and hard work, but good rendering, to make the result believable. Stanford, Max Planck and Erlangen-Nuremberg researchers have […]

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Gait recognition using convolutional neural networks

March 7, 2016

Walk like an Egyptian: computer vision and walking identification

Researchers from the University of Malaga and Cordoba have studied gait recognition. Gait is the pattern of movement of the limbs of animals, including humans, during locomotion over a solid substrate. The goal of gait recognition is to identify people by the way they walk. This biometric approach is performed at a distance, and does […]

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February 19, 2016

Can we still avoid automatic face detection?

After decades of research, automatic face detection and recognition systems are now reliable and widespread. Of course, the result of this is that the users who wish to avoid automatic recognition are becoming less capable of doing so. We currently live in a technology-dependent society, where everyone carries a cellphone with a camera in their […]

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Gaining structural visual knowledge

December 4, 2015

Sherlock: modeling structured knowledge from images

Researchers from the Rutgers University have decided to build a machine-learning method that can continuously gain structured visual knowledge by learning structured facts?

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