While many of these datasets include public figures such as politicans, athletes, and actors; they also include many non-public figures including digital activists, students, pedestrians, and people's semi-private shared photo albums. Some images are used with creative commons licenses, yet others were taken in unconstrained scenarios without awareness or consent. At first glance it appears many of the datasets were created for seemingly harmless academic research studies, but when examined further it becomes clear that they're also used by defense contractors in foreign countries.

During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is helping to power the global facial recognition industry.

MegaPixels is art and research by Adam Harvey about publicly available facial recognition datasets that aims to unravel their histories, futures, geographies, and contents. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets.

The MegaPixels website is produced in partnership with Mozilla who provided the funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies.

Brainwash is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms

Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" +

Brainwash is a dataset of webcam images from the Brainwash Cafe in San Francisco

The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms

Brainwash Dataset

(PAGE UNDER DEVELOPMENT)

Brainwash is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe 1". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them.

diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 4fbd06a5..477673e2 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -4,7 +4,7 @@ MegaPixels - + @@ -26,7 +26,7 @@

Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition.

It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004. +

Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos

It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms.

Created

2002 – 2004

Images

13,233

Identities

5,749

Origin

Yahoo! News Images

Used by

Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA

Website

umass.edu

There are about 3 men for every 1 woman in the LFW dataset 1
The person with the most images is George W. Bush with 530

MegaPixels

MARS is a dataset of people...

MARS includes... +

The Motion Analysis and Re-identification Set (MARS) is a MARS dataset is collection of CCTV footage

The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms

MARS

(PAGE UNDER DEVELOPMENT)

At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

-- cgit v1.2.3-70-g09d2 From b8056f1c85d796146c4dc2d1c6d9d1154313164f Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 11 Mar 2019 01:09:43 +0100 Subject: update text, ars --- site/content/pages/datasets/mars/index.md | 2 +- site/public/datasets/mars/index.html | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/datasets/mars/index.md b/site/content/pages/datasets/mars/index.md index 30c9a4d7..ce5d797d 100644 --- a/site/content/pages/datasets/mars/index.md +++ b/site/content/pages/datasets/mars/index.md @@ -2,7 +2,7 @@ status: published title: MARS -desc: The Motion Analysis and Re-identification Set (MARS) is a MARS dataset is collection of CCTV footage +desc: The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage subdesc: The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms slug: mars cssclass: dataset diff --git a/site/public/datasets/mars/index.html b/site/public/datasets/mars/index.html index d6f2eeff..37e4446a 100644 --- a/site/public/datasets/mars/index.html +++ b/site/public/datasets/mars/index.html @@ -4,7 +4,7 @@ MegaPixels - + @@ -26,7 +26,7 @@

The Motion Analysis and Re-identification Set (MARS) is a MARS dataset is collection of CCTV footage

The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms +

The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage

The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms

MARS

(PAGE UNDER DEVELOPMENT)

-- cgit v1.2.3-70-g09d2 From bc9b135a897dfe91207b2fa5ec600868e2054e02 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 11 Mar 2019 12:04:41 +0100 Subject: text edits --- site/content/pages/about/index.md | 10 +++++----- site/content/pages/datasets/mars/index.md | 4 ++-- site/public/about/index.html | 10 +++++----- site/public/datasets/mars/index.html | 4 ++-- 4 files changed, 14 insertions(+), 14 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index 9c66fbc4..daeb6dd5 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -25,17 +25,17 @@ authors: Adam Harvey (PAGE UNDER DEVELOPMENT) -

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on social media sites, CCTV camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

While many of these datasets include public figures such as politicians, athletes, and actors; they also include many non-public figures including digital activists, students, pedestrians, and people's semi-private shared photo albums. Some images are used with creative commons licenses, yet others were taken in unconstrained scenarios without awareness or consent. At first glance it appears many of the datasets were created for seemingly harmless academic research, but when examined further it becomes clear that they're also used by foreign defense agencies. -During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is helping to power the global facial recognition industry. +During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry. -MegaPixels is art and research by Adam Harvey about publicly available facial recognition datasets that aims to unravel their histories, futures, geographies, and contents. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets. +MegaPixels is art and research by Adam Harvey about publicly available facial recognition datasets that aims to unravel their histories, futures, geographies, and context. Throughout 2019 this site, coded and designed by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets. -The MegaPixels website is produced in partnership with [Mozilla](https://mozilla.org) who provided the funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies. +The MegaPixels website is produced in partnership with [Mozilla](https://mozilla.org) who provided funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies. -The MegaPixels site is based on an [earlier installation](https://ahprojects.com/megapixels-glassroom), also supported by Mozilla, at the [Tactical Tech Glassroom](https://theglassroom.org/) in London about the facial recognition datasets; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets. +The MegaPixels site is based on an earlier [installation](https://ahprojects.com/megapixels-glassroom) (also supported by Mozilla) at the [Tactical Tech Glassroom](https://theglassroom.org/) in London in 2017; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets in 2018, and research during [CV Dazzle](https://cvdazzle.com) from 2010-2015. Through the many prototypes, conversations, pitches, PDFs, and false starts this project has endured during the last 5 years, it eventually evolved into something much different than originally imagined. Now, as datasets become increasingly influential in shaping the computational future, it's clear that they must be critically analyzed to understand the biases, shortcomings, funding sources, and contributions to the surveillance industry. However, it's misguided to only criticize these datasets for their flaws without also praising their contribution to society. Without publicly available facial analysis datasets there would be less public discourse, less open-source software, and less peer-reviewed research. Public datasets can indeed become a vital public good for the information economy but as this projects aims to illustrate, many ethical questions arise about consent, intellecture property, surveillance, and privacy. ### MegaPixels Team diff --git a/site/content/pages/datasets/mars/index.md b/site/content/pages/datasets/mars/index.md index ce5d797d..864dbe5b 100644 --- a/site/content/pages/datasets/mars/index.md +++ b/site/content/pages/datasets/mars/index.md @@ -3,7 +3,7 @@ status: published title: MARS desc: The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage -subdesc: The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms +subdesc: The MARS dataset includes 1,191,003 of people used for training person re-identification algorithms slug: mars cssclass: dataset image: assets/background.jpg @@ -21,7 +21,7 @@ authors: Adam Harvey + Faces: TBD -## MARS +## Motion Analysis and Re-identification Set (MARS) (PAGE UNDER DEVELOPMENT) diff --git a/site/public/about/index.html b/site/public/about/index.html index 8a95825d..8c437c4b 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -36,11 +36,11 @@

(PAGE UNDER DEVELOPMENT)

The MegaPixels site is based on an earlier installation, also supported by Mozilla, at the Tactical Tech Glassroom in London about the facial recognition datasets; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets.

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

MegaPixels is art and research by Adam Harvey about publicly available facial recognition datasets that aims to unravel their histories, futures, geographies, and context. Throughout 2019 this site, coded and designed by Jules LaPlace, will publish research reports, visualizations, downloadable statistics, and interactive tools for searching the datasets.

The MegaPixels website is produced in partnership with Mozilla who provided funding to research the datasets, build the site, and develop tools to help you understand the role these datasets have played in creating biometric surveillance technologies.

The MegaPixels site is based on an earlier installation (also supported by Mozilla) at the Tactical Tech Glassroom in London in 2017; and a commission from the Elevate arts festival curated by Berit Gilma about pedestrian recognition datasets in 2018, and research during CV Dazzle from 2010-2015. Through the many prototypes, conversations, pitches, PDFs, and false starts this project has endured during the last 5 years, it eventually evolved into something much different than originally imagined. Now, as datasets become increasingly influential in shaping the computational future, it's clear that they must be critically analyzed to understand the biases, shortcomings, funding sources, and contributions to the surveillance industry. However, it's misguided to only criticize these datasets for their flaws without also praising their contribution to society. Without publicly available facial analysis datasets there would be less public discourse, less open-source software, and less peer-reviewed research. Public datasets can indeed become a vital public good for the information economy but as this projects aims to illustrate, many ethical questions arise about consent, intellecture property, surveillance, and privacy.

MegaPixels Team

Adam Harvey is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and is a researcher in residence at Karlsruhe HfG.
ahprojects.com

Jules LaPlace is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians.
asdf.us

diff --git a/site/public/datasets/mars/index.html b/site/public/datasets/mars/index.html index 37e4446a..bfad52a3 100644 --- a/site/public/datasets/mars/index.html +++ b/site/public/datasets/mars/index.html @@ -26,8 +26,8 @@

The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage

The MARS dataset includes 1,191,003 of people and is used for training person re-identification algorithms -

MARS

The Motion Analysis and Re-identification Set (MARS) is a dataset is collection of CCTV footage

The MARS dataset includes 1,191,003 of people used for training person re-identification algorithms +

Motion Analysis and Re-identification Set (MARS)

(PAGE UNDER DEVELOPMENT)

Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

-- cgit v1.2.3-70-g09d2 From 092d47ca0a005e5700bee86ec72e2206acdc5fc1 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 11 Mar 2019 12:08:49 +0100 Subject: text edits --- site/content/pages/about/index.md | 8 +++++--- site/public/about/index.html | 3 ++- 2 files changed, 7 insertions(+), 4 deletions(-) (limited to 'site/content/pages') diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index daeb6dd5..5738d5ce 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -35,8 +35,6 @@ MegaPixels is art and research by Adam HarveyDuring the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry.

MegaPixels Team

Additional Researchers

Additional research by Berit Gilma.

Project History

-- cgit v1.2.3-70-g09d2 From 1fe0e5c79c3cbc4b13083116980e62b449866100 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Tue, 12 Mar 2019 01:18:12 +0100 Subject: add credits, 2col about --- site/assets/css/css.css | 40 ++++++++++++ site/content/pages/about/credits.md | 43 ++++++++++++ site/content/pages/about/disclaimer.md | 1 + site/content/pages/about/index.md | 48 +++++++------- site/content/pages/about/press.md | 1 + site/content/pages/about/privacy.md | 1 + site/content/pages/about/terms.md | 1 + .../pages/research/00_introduction/index.md | 16 +++++ site/public/about/credits/index.html | 76 ++++++++++++++++++++++ site/public/about/disclaimer/index.html | 1 + site/public/about/index.html | 32 +++++---- site/public/about/press/index.html | 1 + site/public/about/privacy/index.html | 1 + site/public/about/terms/index.html | 1 + site/public/research/00_introduction/index.html | 12 +++- 15 files changed, 237 insertions(+), 38 deletions(-) create mode 100644 site/content/pages/about/credits.md create mode 100644 site/public/about/credits/index.html (limited to 'site/content/pages') diff --git a/site/assets/css/css.css b/site/assets/css/css.css index a0f9519b..69302409 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -481,6 +481,46 @@ section.fullwidth .image { color:#fff; border: 0; } + + +/* about page */ + +.flex-container { + padding: 0; + margin: 0; + list-style: none; + + display: -webkit-box; + display: -moz-box; + display: -ms-flexbox; + display: -webkit-flex; + display: flex; + + -webkit-flex-flow: row wrap; + justify-content: space-around; +} + +.team-member { + height: auto; + margin-top: 10px; + color: white; + width: 400px; + font-weight: bold; + flex-grow: 1; + margin:0 40px 0 0; +} +.team-member&:last-child{ + margin:0 0 0 40px; +} +.team-member p{ + font-size:14px; +} +.team-member img{ + margin:0; + display: block; +} + + .sideimage { margin: 0px 0 40px 0; display: flex; diff --git a/site/content/pages/about/credits.md b/site/content/pages/about/credits.md new file mode 100644 index 00000000..3ad962df --- /dev/null +++ b/site/content/pages/about/credits.md @@ -0,0 +1,43 @@ +------------ + +status: published +title: MegaPixels Press and News +desc: MegaPixels Press and News +slug: press +cssclass: about +published: 2018-12-04 +updated: 2018-12-04 +authors: Adam Harvey + +------------ + +# Credits + + + + +#### Team + +- Research, concept: Adam Harvey +- Site development, visualizations: Jules LaPlace +- Assistant researcher: Berit Gilma +- Produced in Partnership with Mozilla + +#### Code + +- This site uses D3 and C2 for visuzations. +- Add more here + +#### Data + +- link to github +- how it was gathered \ No newline at end of file diff --git a/site/content/pages/about/disclaimer.md b/site/content/pages/about/disclaimer.md index 314675ee..f82a09a0 100644 --- a/site/content/pages/about/disclaimer.md +++ b/site/content/pages/about/disclaimer.md @@ -17,6 +17,7 @@ authors: Adam Harvey

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

Adam Harvey

MegaPixels is art and research by Adam Harvey about facial recognition datasets that aims to unravel their histories, futures, geographies, and meanings. Throughout 2019 this site, coded by Jules LaPlace, will publish research reports, visualizations, raw data, and interactive tools to explore how publicly available facial recognition datasets contribute to a global supply chain of biometric data that powers the global facial recognition industry.

Adam Harvey

is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund grants, and is a researcher in residence at Karlsruhe HfG. +
+ ahprojects.com +

Jules LaPlace

is an American creative technologist also based in Berlin. He was previously the CTO of a digital agency in NYC and now also works at VFRAME, developing computer vision for human rights groups. Jules also builds creative software for artists and musicians. +
+ https://asdf.us +

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

videos on YouTube

MegaPixels

+ +

MegaPixels

+ +

+ Datasets + About +

+ +

Credits

Team

Research, concept: Adam Harvey
Site development, visualizations: Jules LaPlace
Assistant researcher: Berit Gilma
Produced in Partnership with Mozilla

Code

This site uses D3 and C2 for visuzations.
Add more here

Data

link to github
how it was gathered

+ +

About
Press
Credits
Disclaimer
Terms and Conditions
Privacy Policy

(PAGE UNDER DEVELOPMENT)

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to the development and evaluation face recognition technology. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

MegaPixels Team

Additional Researchers

Additional research by Berit Gilma.

Project History

The MegaPixels website is produced in partnership with Mozilla.

Brainwash Dataset

MARS

MARS

MegaPixels Team

MARS

Motion Analysis and Re-identification Set (MARS)

MegaPixels Team

Additional Researchers

Project History

Adam Harvey

Jules LaPlace

Credits

Team

Code

Data

MegaPixels Team

Additional Researchers

Project History

Adam Harvey

Jules LaPlace

Motivation