For Your Eyes Only
Or, when is an apple no longer an apple?
This project will explore the aesthetics of visual obscurity in an era of machine learning and computer vision. The result of this exploration will be the production of a series of objects for human eyes only: objects that cannot be recognized by computer vision, but can still be recognized by humans.
For example, in the image above I am clearly holding an apple. However when I submit this image to a Google Image search, the results are obscured. It no longer appears as an apple to algorithms. By contrast, an image of a conventional apple yields the correct result.
Test: Is This An Apple?
To illustrate this concept I used a conventional apple and covered one side with dots, leaving the other side unaltered.
The Google search results for each object are shown below.
In this project I will use machine learning algorithms to build a computer vision profile for recognizing an object. Since the profile constitutes a definition of what the object is, the profile can also be used to define what it is not.
The first For Your Eyes Only (FYEO) object trial will be borne from a conventional apple. However, instead of the conventional interpretation of the apple as a forbidden fruit, this FYEO object will represent biological evolution towards anonymity and visual obscurity, camouflage from machines. A possible trait that I imagine could be useful in the future, when cameras and machine learning are even more ubiquitous.
In this way, visual obscurity can also be a type of camouflage or deception, which historian Roy Behrens notes “has always been critical to daily survival—for human and non-human creatures alike—and, judging by its current ubiquity, there is no end in immediate sight”.
There is additional support for the philosophical value of visual obscurity in Baudrillard’s statement that, “[t]he moment a thing is named, the moment representation and concepts take hold of it, is the moment when it begins to lose its energy”.
The goal of this project is to create something in between, an object that can be both detectable and obscure, evolving new visual mutations that satisfy human perception and override machine vision.
To build the FYEO object series, I will be creating machine learning algorithms to generate visual mutations of objects that are robust to object recognition. The final objects will be 3D modeled and printed.
The final 3D printed objects will be presented in a custom case accompanied by a collection of images showing the evolution of the objects’ mutations.
With support from Rhizome, my proposed project will be executed in a year or less. The following is an estimated timeline for research, prototyping and production:
- Stage 1: Create object-detection profile for apple using eblearn
- Stage 2: Develop machine-learning algorithms to deconstruct the object-profile
- Stage 3: Generate prototypical 3D models to test
- Stage 4: Fabricate 3D models
- Research: $1,000 (est. 3 months)
- Development: $1,500 (est. 3 months)
- Assistants and Developers: $500
- Production: $500 (est. 1 month)
- CV Dazzle
Makeup and hair styling used as camouflage from face detection
This project uses a custom developed computer vision library built on top of OpenCV to create camouflage from face detection
UDATE May 16: As part of the preliminary research for this project, I’ve prepared a basic reverse-engineered face using a similar method.
The FYEO Objects project will adopt a similar approach of reverse engineering an object detection profile, though will extend this concept to 3D forms.
- 2008-2010 Masters of Professional Studies, Interactive Telecommunications Program, NYU
- 1999-2004 Bachelor of Arts, Integrative Arts, Pennsylvania State University
- 2012 Woodstock Digital Media Festival VT (upcoming)
- 2012 Voegele Kultur Zentrum – D.E.F.E.N.C.E.
- 2012 On Stellar Rays – FaceTime
- 2010 NoiseBridge – Anti-Surveillance Fashion Show
- 2012 CNN.com – How to hide from face-detection technology
- 2012 Der Standard – Wie man Gesichtserkennung austricksen kann
- 2012 Government Computer News – WWI ‘dazzle paint’ fools face recognition scanners
- 2012 Wired Magazine – How to use camouflage to thwart facial recognition
- 2011 NYTimes.com – How to Camouflage Yourself From Face Recognition Technology
- 2011 Der Spiegel – Look at me – and I know who you are
- 2010 Reuters – Video
- 2012 SPOOFING AND ANTI-SPOOFING: THE WIDER HUMAN CONTEXT – At the Centre for Science, Society and Citizenship, Rome
- 2012 Philadelphia Science Festival – Hiding in Plain Sight
- 2012 Deutschlandradio Kultur – Camouflage für den Alltag
- 2012 Makematics – On Viola Jones Face Detection
- 2011 The Art Blog – The Anti Face
- 2011PopTech.org – 6 Questions
- 2010 HOPE Hackers Conference – Face Deception