From 2c6d30bae390cb1cbe4db3014c4d7322b58ae2bb Mon Sep 17 00:00:00 2001 From: adamhrv Date: Tue, 19 Mar 2019 12:20:52 +0100 Subject: updating pages --- site/content/pages/about/index.md | 4 +- .../pages/datasets/brainwash/assets/background.jpg | Bin 86425 -> 78860 bytes .../datasets/brainwash/assets/background_540.jpg | Bin 0 -> 83594 bytes .../datasets/brainwash/assets/background_600.jpg | Bin 0 -> 86425 bytes site/content/pages/datasets/brainwash/index.md | 13 +++--- site/content/pages/datasets/mars/index.md | 2 +- .../research/01_from_1_to_100_pixels/index.md | 3 +- .../research/02_what_computers_can_see/index.md | 51 +++++++++++++++++++++ 8 files changed, 64 insertions(+), 9 deletions(-) mode change 100755 => 100644 site/content/pages/datasets/brainwash/assets/background.jpg create mode 100644 site/content/pages/datasets/brainwash/assets/background_540.jpg create mode 100755 site/content/pages/datasets/brainwash/assets/background_600.jpg (limited to 'site/content/pages') diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md index 3dd14bfe..4fec0777 100644 --- a/site/content/pages/about/index.md +++ b/site/content/pages/about/index.md @@ -26,7 +26,9 @@ authors: Adam Harvey (PAGE UNDER DEVELOPMENT) -

Ever since government agencies began researching face recognition in the early 1960's, datasets of face images have always been central to technological advancements. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance cameras on college campuses, search engine queries for celebrities, cafe livestreams, or personal videos posted on YouTube. Collectively, facial recognition datasets are now gathered "in the wild".

+

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

+ +Collectively, facial recognition datasets are now gathered "in the wild".

MegaPixels is art and research by Adam Harvey about facial recognition datasets that unravels their histories, futures, geographies, and meanings. Throughout 2019 this site this site 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.

diff --git a/site/content/pages/datasets/brainwash/assets/background.jpg b/site/content/pages/datasets/brainwash/assets/background.jpg old mode 100755 new mode 100644 index 8f2de697..e6393ab5 Binary files a/site/content/pages/datasets/brainwash/assets/background.jpg and b/site/content/pages/datasets/brainwash/assets/background.jpg differ diff --git a/site/content/pages/datasets/brainwash/assets/background_540.jpg b/site/content/pages/datasets/brainwash/assets/background_540.jpg new file mode 100644 index 00000000..5c8c0ad4 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/background_540.jpg differ diff --git a/site/content/pages/datasets/brainwash/assets/background_600.jpg b/site/content/pages/datasets/brainwash/assets/background_600.jpg new file mode 100755 index 00000000..8f2de697 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/background_600.jpg differ diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index a01f5bf4..816485d7 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -2,7 +2,7 @@ status: published title: Brainwash -desc: Brainwash is a dataset of webcam images from the Brainwash Cafe in San Francisco +desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms slug: brainwash cssclass: dataset @@ -17,18 +17,16 @@ authors: Adam Harvey ### sidebar -+ Collected: 2014 + Published: 2015 + Images: 11,918 + Faces: 91,146 + Created by: Stanford Department of Computer Science + Funded by: Max Planck Center for Visual Computing and Communication -+ Resolution: 640x480px -+ Size: 4.1GB -+ Origin: Brainwash Cafe, San Franscisco ++ Location: Brainwash Cafe, San Franscisco + Purpose: Training face detection + Website: stanford.edu + Paper: End-to-End People Detection in Crowded Scenes ++ Explicit Consent: No ## Brainwash Dataset @@ -45,9 +43,12 @@ Since it's publication by Stanford in 2015, the Brainwash dataset has appeared i ![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) +{% include 'chart.html' %} + {% include 'map.html' %} -{% include 'chart.html' %} +Add more analysis here + {% include 'supplementary_header.html' %} diff --git a/site/content/pages/datasets/mars/index.md b/site/content/pages/datasets/mars/index.md index 864dbe5b..2b3192f3 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 dataset is collection of CCTV footage +desc: 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 used for training person re-identification algorithms slug: mars cssclass: dataset diff --git a/site/content/pages/research/01_from_1_to_100_pixels/index.md b/site/content/pages/research/01_from_1_to_100_pixels/index.md index 477bd1a1..a7b863a9 100644 --- a/site/content/pages/research/01_from_1_to_100_pixels/index.md +++ b/site/content/pages/research/01_from_1_to_100_pixels/index.md @@ -54,4 +54,5 @@ Ideas: [^nist_sres]: NIST 906932. Performance Assessment of Face Recognition Using Super-Resolution. Shuowen Hu, Robert Maschal, S. Susan Young, Tsai Hong Hong, Jonathon P. Phillips -- "Note that we only keep the images with a minimal side length of 80 pixels." and "a face will be labeled as “Ignore” if it is very difficult to be detected due to blurring, severe deformation and unrecognizable eyes, or the side length of its bounding box is less than 32 pixels." Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf \ No newline at end of file +- "Note that we only keep the images with a minimal side length of 80 pixels." and "a face will be labeled as “Ignore” if it is very difficult to be detected due to blurring, severe deformation and unrecognizable eyes, or the side length of its bounding box is less than 32 pixels." Ge_Detecting_Masked_Faces_CVPR_2017_paper.pdf +- IBM DiF: "Faces with region size less than 50x50 or inter-ocular distance of less than 30 pixels were discarded. Faces with non-frontal pose, or anything beyond being slightly tilted to the left or the right, were also discarded." diff --git a/site/content/pages/research/02_what_computers_can_see/index.md b/site/content/pages/research/02_what_computers_can_see/index.md index c289e16b..ab4c7884 100644 --- a/site/content/pages/research/02_what_computers_can_see/index.md +++ b/site/content/pages/research/02_what_computers_can_see/index.md @@ -99,3 +99,54 @@ A list of 100 things computer vision can see, eg: - Wearing Earrings - Wearing Necktie - Wearing Necklace + + +## From Market 1501 + +The 27 attributes are: + +| attribute | representation in file | label | +| :----: | :----: | :----: | +| gender | gender | male(1), female(2) | +| hair length | hair| short hair(1), long hair(2) | +| sleeve length | up | long sleeve(1), short sleeve(2) | +| length of lower-body clothing | down | long lower body clothing(1), short(2) | +| type of lower-body clothing| clothes| dress(1), pants(2) | +| wearing hat| hat | no(1), yes(2) | +| carrying backpack| backpack | no(1), yes(2) | +| carrying bag| bag | no(1), yes(2) | +| carrying handbag| handbag | no(1), yes(2) | +| age| age | young(1), teenager(2), adult(3), old(4) | +| 8 color of upper-body clothing| upblack, upwhite, upred, uppurple, upyellow, upgray, upblue, upgreen | no(1), yes(2) | +| 9 color of lower-body clothing| downblack, downwhite, downpink, downpurple, downyellow, downgray, downblue, downgreen,downbrown | no(1), yes(2) | + +source: https://github.com/vana77/Market-1501_Attribute/blob/master/README.md + +## From DukeMTMC + +The 23 attributes are: + +| attribute | representation in file | label | +| :----: | :----: | :----: | +| gender | gender | male(1), female(2) | +| length of upper-body clothing | top | short upper body clothing(1), long(2) | +| wearing boots| boots| no(1), yes(2) | +| wearing hat| hat | no(1), yes(2) | +| carrying backpack| backpack | no(1), yes(2) | +| carrying bag| bag | no(1), yes(2) | +| carrying handbag| handbag | no(1), yes(2) | +| color of shoes| shoes | dark(1), light(2) | +| 8 color of upper-body clothing| upblack, upwhite, upred, uppurple, upgray, upblue, upgreen, upbrown | no(1), yes(2) | +| 7 color of lower-body clothing| downblack, downwhite, downred, downgray, downblue, downgreen, downbrown | no(1), yes(2) | + +source: https://github.com/vana77/DukeMTMC-attribute/blob/master/README.md + +## From H3D Dataset + +The joints and other keypoints (eyes, ears, nose, shoulders, elbows, wrists, hips, knees and ankles) +The 3D pose inferred from the keypoints. +Visibility boolean for each keypoint +Region annotations (upper clothes, lower clothes, dress, socks, shoes, hands, gloves, neck, face, hair, hat, sunglasses, bag, occluder) +Body type (male, female or child) + +source: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/h3d/ \ No newline at end of file -- cgit v1.2.3-70-g09d2