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-------------
-
-status: draft
-title: What Computers Can See
-desc: What Computers Can See
-slug: what-computers-can-see
-published: 2018-12-15
-updated: 2018-12-15
-authors: Adam Harvey
-sync: false
-
-------------
-
-# What Computers Can See About Your Face
-
-
-A list of 100 things computer vision can see, eg:
-
-- age, race, gender, ancestral origin, body mass index
-- eye color, hair color, facial hair, glasses
-- beauty score, 
-- intelligence
-- what you're looking at
-- medical conditions
-- tired, drowsiness in car
-- affectiva: interest in product, intent to buy
-
-## From SenseTime paper
-
-Exploring Disentangled Feature Representation Beyond Face Identification
-
-From https://arxiv.org/pdf/1804.03487.pdf
-The attribute IDs from 1 to 40 corre-spond to: ‘5 o Clock Shadow’, ‘Arched Eyebrows’, ‘Attrac-tive’, ‘Bags Under Eyes’, ‘Bald’, ‘Bangs’, ‘Big Lips’, ‘BigNose’, ‘Black Hair’, ‘Blond Hair’, ‘Blurry’, ‘Brown Hair’,‘Bushy Eyebrows’, ‘Chubby’, ‘Double Chin’, ‘Eyeglasses’,‘Goatee’,  ‘Gray  Hair’,  ‘Heavy  Makeup’,  ‘High  Cheek-bones’, ‘Male’, ‘Mouth Slightly Open’, ‘Mustache’, ‘Nar-row Eyes’,  ‘No Beard’,  ‘Oval Face’,  ‘Pale Skin’,  ‘PointyNose’,  ‘Receding  Hairline’,  ‘Rosy  Cheeks’,  ‘Sideburns’,‘Smiling’,  ‘Straight  Hair’,  ‘Wavy  Hair’,  ‘Wearing  Ear-rings’, ‘Wearing Hat’, ‘Wearing Lipstick’, ‘Wearing Neck-lace’, ‘Wearing Necktie’ and ‘Young’. It’
-
-
-## From PubFig Dataset
-
-- Male
-- Asian
-- White
-- Black
-- Baby
-- Child
-- Youth
-- Middle Aged
-- Senior
-- Black Hair
-- Blond Hair
-- Brown Hair
-- Bald
-- No Eyewear
-- Eyeglasses
-- Sunglasses
-- Mustache
-- Smiling Frowning
-- Chubby
-- Blurry
-- Harsh Lighting
-- Flash
-- Soft Lighting
-- Outdoor Curly Hair
-- Wavy Hair
-- Straight Hair
-- Receding Hairline
-- Bangs
-- Sideburns
-- Fully Visible Forehead 
-- Partially Visible Forehead 
-- Obstructed Forehead
-- Bushy Eyebrows 
-- Arched Eyebrows
-- Narrow Eyes
-- Eyes Open
-- Big Nose
-- Pointy Nose
-- Big Lips
-- Mouth Closed
-- Mouth Slightly Open
-- Mouth Wide Open
-- Teeth Not Visible
-- No Beard
-- Goatee 
-- Round Jaw
-- Double Chin
-- Wearing Hat
-- Oval Face
-- Square Face
-- Round Face 
-- Color Photo
-- Posed Photo
-- Attractive Man
-- Attractive Woman
-- Indian
-- Gray Hair
-- Bags Under Eyes
-- Heavy Makeup
-- Rosy Cheeks
-- Shiny Skin
-- Pale Skin
-- 5 o' Clock Shadow
-- Strong Nose-Mouth Lines
-- Wearing Lipstick
-- Flushed Face
-- High Cheekbones
-- Brown Eyes
-- Wearing Earrings
-- Wearing Necktie
-- Wearing Necklace
-
-for i in {1..9};do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_0$i.MP4;done;for i in {10..20}; do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_$i.MP4;done
-
-## 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/
-
-## From Leeds Sports Pose
-
-=INDEX(A2:A9,MATCH(datasets!D1,B2:B9,0))
-=VLOOKUP(A2, datasets!A:J, 7, FALSE)
-
-Right ankle
-Right knee
-Right hip
-Left hip
-Left knee
-Left ankle
-Right wrist
-Right elbow
-Right shoulder
-Left shoulder
-Left elbow
-Left wrist
-Neck
-Head top
-
-source: http://web.archive.org/web/20170915023005/sam.johnson.io/research/lsp.html
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