Face Tracker and Mind Control Machine

Questions, speculations & updates on the techniques and nature of media fakery

Face Tracker and Mind Control Machine

Unread postby AnonymousTruther2 on Tue Oct 04, 2011 3:31 am

Until now, if you wanted to understand the inner-workings of your brain, you had to slide into a huge, expensive and claustrophobic CT machine. But now a device with the simplicity of a head massager can read the electrical activity deep inside your melon and relay those commands to any number of devices.

It is the $300 Emotive Epic headset, and it could change how paraplegics move, soldiers shoot and the lazy change channels. But Emotive's founder and inventor thinks it can help understand and cure diseases from autism to epilepsy.
(link: http://emotiv.com/)

Until there is mind-control romance, we take a look at the bubbliest trend in on-line dating; location-based social apps. After Joel Simkhai created a gay hook-up app called Grindr, he says countless women begged him for a straight version.

With Blendr, anyone can create a profile, check in and see how many fellow dog/sushi/"Mad Men"-loving singles are within walking distance. Now if he can just convince all women that "proximity" is a turn on.

Anyone who has tried online dating can attest that profile photos and reality don't often match.

But while Skype and Facetime make it harder to hide the real you, Jason Siraghi's Face Tracker algorithm changes the game once again. It allows anyone with a web camera to "wear" another face in real time. The edges are still rough, but as more coders jump in and perfect the software, it is only a matter of time before a scandal-plagued celeb uses the "someone stole my face" defense.

watch the video at 1:40

FaceTracker is a C/C++ API for real time generic non-rigid face alignment and tracking.

Non-rigid face alignment and tracking is a common problem in computer vision. It is the front-end to many algorithms that require registration, for example face and expression recognition. However, those working on algorithms for these higher level tasks are often unfamiliar with the tools and peculiarities regarding non-rigid registration (i.e. pure machine learning scientists, psychologists, etc.). Even those directly working on face alignment and tracking often find implementing an algorithm from published work to be a daunting task, not least because baseline code against which performance claims can be assessed does not exist. As such, the goal of FaceTracker is to provide source code and pre-trained models that can be used out-of-the-box, for the dual purpose of:

1. Promoting the advancement of higher level inference algorithms that require registration.

2. Providing baseline code to promote quantitative improvements in face registration.


• Real time: ranging from 20-30 fps (depending on processor, compiler and use of OpenMP)

• Generic: designed to work for most people under most conditions

• No training required: a pre-trained model is provided

• Detection based initialisation: no user intervention required

• Automatic failure detection: requires no user re-initialisation

• Camera or video input

FaceTracker is available for download (for research purposes only). The library includes the C/C++ API, example code for interfacing with the API, a pre-trained model and documentation. To download it, please send an email to Jason Saragih (Jason.saragih@csiro.au).

The Tracker:
The code requires OpenCV 2.0 and the provided model was trained using the MultiPIE database. The tracker is based on a modified version of the constrained local model described in:

J. Saragih, S. Lucey and J. Cohn, ``Deformable Model Fitting by Regularized Landmark Mean-Shifts", International Journal of Computer Vision (IJCV)

People Using FaceTracker:

Some people are using FaceTracker to do some really cool stuff:

• FaceOSC

• Face Cloning

• A music Video!

• Face Projection

• Being John Malkovich

• pkmFace

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Joined: Thu Sep 22, 2011 11:17 pm

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