What is color search? • Narrow down items by colors • e.g. One-piece dress & white • e.g. Coat & brown • Detect colors automatically • Sellers input nothing • Color detection from item images
Why we implemented it? • Most users choosing clothing colors • Questionnaire • Interview • Search word logs • To specialize in fashion • Fashion specialized search features
Why 12 colors? • From human color recognition research[1] • All languages have basic 11 color terms • 11 colors are universal • Red, yellow, green, blue, orange, purple, pink, brown, gray, black, white • From search queries including color names • Listed queries in descending order • Merged into basic 11 colors (e.g camel is brown) • Leaved beige because it can't merge [1] Berlin B.and Kay P, “Basic Color Terms:Their Universality and Evolution.”
Color correction by white balancing • Correct colors of images taken under fluorescent lamp • Typical fluorescent lights make images greenish • Fashion images usually taken inside a room • Correct colors with Retinex[2] • A method modeled human visual features • Do not affect photoshopped images [2] E. Land and J. McCann, “Lightness and Retinex theory,”
Remove background • Eliminate the effect of background colors • Make background mask to remove • Make background mask • Detect edges • Flood magenta from corners • Extract magenta regions as background mask
Detect a mode color • Detect a mode color from the central portion • Fashion items usually appear in center of photo • Central portion is less affected by background colors • Detect a mode color • Crop the central portion • Reduce colors into 8 • Composite background mask • Make histogram and detect a mode
Choose nearest color palette • RGB to 12 colors • 255*255*255ʢ16,581,375ʣ → 12 • Use color name survey[3] • 196,608 RGB values are named • We converted to HSL and used the range of each color names • Choose nearest color palette • Conver RGB to HSL • Choose nearest palette considering HSL range IUUQCMPHYLDEDPNDPMPSTVSWFZSFTVMUT
Accuracy of color detection • Checked 30 items visually in major categories • Average is 48.36% • Well appeared colors are well • Black: 90.67% • Red: 79.33% • Pink: 72.67% • White: 56.67% • Less appeared colors affected by false detection of other colors
Item found ratio in search result • We defined item found proportion • Percentage of users who opened a item in search result • Item found • Keyword search: about 69% • Color search: about 75% • Color search become easier to find items than keyword search
Summary • We implemented color search • Researched user buying behavior and implemented fashion specialized search • Color palette were created from human recognition research and search queries • Correcting color, removing background, cropping center and detect nearest color palette • Color search become easier to find items than keyword search
shoby
hato3isfriend
soracom
marikashiotsuki
sprasiainc
interu
kojira
red_frasco
trycycle
netmarkjp
k9i
nabedge
zakiyama
kevinliebholz
productmarketing
reverentgeek
notwaldorf
skipperchong
mraible
phodgson
dougneiner
chrislema
aarron
maltzj
sachag