Systems and methods for wardrobe management
US-10282772-B2 · May 7, 2019 · US
US2019188773A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2019188773-A1 |
| Application number | US-201715847747-A |
| Country | US |
| Kind code | A1 |
| Filing date | Dec 19, 2017 |
| Priority date | Dec 19, 2017 |
| Publication date | Jun 20, 2019 |
| Grant date | — |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
The disclosure relates to determining thermal insulation levels of clothing a user should wear when traveling to a destination. To do this, a thermal insulation level of clothing worn by a user and levels worn by a crowd can be analyzed from images including the user or the crowd. A thermal sensitivity bias for the user can be determined by comparing those levels for similar locations. Environment data can then be collected for the destination. A thermal insulation level of clothing worn by the crowd for the destination can be predicted based on the environment data. This level can be adjusted with the bias for the user to generate a thermal insulation level of clothing to be worn by the user at the destination. An image having clothing with that level can be displayed to recommend a style of clothing for the user to wear at the destination.
Opening claim text (preview).
We claim: 1 . A method for determining thermal insulation levels for clothing at a computer or mobile device, comprising: analyzing a thermal insulation level of clothing worn by a user in one or more images including the user and a crowd of individuals; analyzing a thermal insulation level of clothing worn by the crowd of individuals in the one or more images; determining a thermal sensitivity bias for the user by comparison of the thermal insulation level of clothing worn by the user to the thermal insulation level of clothing worn by the crowd; collecting environment data based on at least one of time and location of a destination from a database; predicting a thermal insulation level of clothing worn by the crowd for the destination based on the destination and the collected environment data; generating a thermal insulation level of clothing worn by the user at the destination comprised of the thermal insulation level of the clothing worn by the crowd for the destination adjusted by the thermal sensitivity bias for the user; identifying an image from the database having clothing with a thermal insulation level comparable to the thermal insulation level of clothing worn by the user at the destination; and recommending a style of clothing to the user using a computer or mobile device based on the identified image. 2 . The method of claim 1 , further comprising: collecting past environment, time and location data from one or more images including the user and/or a crowd of individuals; and correlating the past environment, time and location data to a thermal insulation level of clothing worn by the user or crowd of individuals in the same image. 3 . The method of claim 1 , wherein: the one or more images include the user in each of a plurality of the one or more images; the one or more images include the crowd of individuals in each of a plurality of the one or more images; or the one or more images include the user and the crowd of individuals at a same location and at the same time of year in each of a plurality of the one or more images. 4 . The method of claim 1 , wherein determining the thermal sensitivity bias for the user includes averaging multiple comparisons of thermal insulation levels of clothing worn by the user to thermal insulation levels of clothing worn by the crowd at a same time, location, and environment. 5 . The method of claim 1 , wherein: analyzing the thermal insulation level of clothing worn by the crowd includes inputting the one or more images including the crowd into a trained second model, analyzing the thermal insulation level of clothing worn by the user includes inputting the one or more images including the user into a trained first model, and predicting the thermal insulation level of clothing worn by the crowd at the destination includes inputting the destination and collected environment data into the trained second model. 6 . The method of claim 1 , wherein identifying an image from the database comprises one of: matching the thermal insulation level of clothing worn by the user at the destination with a thermal insulation level of clothing worn by the user in the one or more images including the user; matching the thermal insulation level of clothing worn by the user at the destination with a thermal insulation level of clothing worn by the crowd in the one or more images including the crowd; or matching the thermal insulation level of clothing worn by the user at the destination with a thermal insulation level of clothing in an image from a vendor. 7 . The method of claim 6 , further comprising displaying the image from the vendor to the user, wherein the image from the vendor has a link to a website of the vendor, the website being capable of selling the clothing in the image from the vendor to the user. 8 . The method of claim 6 , wherein recommending a style of clothing to the user includes one of displaying the matched clothing worn by the user in the one or more images including the user, or displaying the matched clothing in the image from a vendor when the clothing in the image from a vendor was previously viewed at a website of the vendor. 9 . The method of claim 1 , wherein the database comprises average thermal insulation levels of clothing worn by the crowd in a plurality of locations, times of year and environments. 10 . The method of claim 1 , wherein: the destination includes one of a trip itinerary, or a trip time and location; the collected environment data includes weather information for the destination; and the destination is at a different location than a location of the user's primary residence. 11 . A determining thermal insulation levels for clothing device, comprising: a memory storage comprising instructions; and one or more processors in communication with the memory storage, wherein the one or more processors execute the instructions to: determine a thermal sensitivity bias for a user by comparison of the thermal insulation level of clothing worn by the user in one or more images including the user and a crowd of individuals to the thermal insulation level of clothing worn by the crowd in the one or more images; collect environment data based on at least one of time and location of a destination from a database; predict a thermal insulation level of clothing worn by the crowd for the destination based on the destination and the collected environment data; generate a thermal insulation level of clothing worn by the user at the destination comprised of the thermal insulation level of the clothing worn by the crowd for the destination adjusted by the thermal sensitivity bias for the user; and identify an image from the database having clothing with a thermal insulation level comparable to the thermal insulation level of clothing worn by the user at the destination. 12 . The device of claim 11 , wherein: the one or more images include the user in each of a plurality of the one or more images; the one or more images include the crowd of individuals in each of a plurality of the one or more images; or the one or more images include the user and the crowd of individuals at a same location and at the same time of year in each of a plurality of the one or more images. 13 . The device of claim 11 , wherein determining the thermal sensitivity bias for the user includes averaging multiple comparisons of thermal insulation levels of clothing worn by the user to thermal insulation levels of clothing worn by the crowd at a same time, location, and environment. 14 . The device of claim 11 , wherein determine a thermal sensitivity bias for the user includes: inputting the one or more images including the crowd into a trained second model to determine the thermal insulation level of clothing worn by the crowd in the one or more images; and inputting the one or more images including the user into a trained first model to determine the thermal insulation level of clothing worn by the user in one or more images including the user and a crowd of individuals to; and wherein predicting the thermal insulation level of clothing worn by the crowd at the destination includes inputting the destination and collected environment data into the trained second model. 15 . The device of claim 11 , wherein identifying an image from the database comprises one of: matching the thermal insulation level of clothing worn by the user at the destination with a thermal insulation level of clothing worn by the user in the one or more images including the user; matching the thermal insulation level of clothing wo
Industrial image inspection · CPC title
Recommending goods or services · CPC title
Fabrics; Textile; Paper · CPC title
Travel agencies · CPC title
by investigating thermal conductivity (by calorimetry G01N25/20; by measuring change of resistance of an electrically-heated body G01N27/18) · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.