Patent · US Active

Computer vision architecture with machine learned image recognition models

US10467501B2 · kind B2 · utility

6Cited by

1References

20Claims

0Family size

Assignee

SAP SE · DE

Inventors

Sivakumar N · Viralimalai, IN
Praveenkumar A K · Bengaluru, IN
Raghavendra D · Kalaburagi, IN
Vijay G · Bengaluru, IN
Pratik Shenoy · Bengaluru, IN
Kishan Kumar Kedia · Yadgir, IN

Key dates

Filing date	Oct 30, 2017
Grant date	Nov 5, 2019
Priority date	—
Expiry date	Feb 16, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG06T2207/30242
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

In an example, a first machine learning algorithm is used to train a smart contour model to identify contours of product shapes in input images and to identify backgrounds in the input images. A second machine learning algorithm is used to train a plurality of shape-specific classification models to output identifications of products in input images. A candidate image of one or more products is obtained. The candidate image is passed to the smart contour model, obtaining output of one or more tags identifying product contours in the candidate image. The candidate image and the one or more tags are passed to an ultra-large scale multi-hierarchy classification system to identify one or more classification models for one or more individual product shapes in the candidate image. The one or more classification models are used to distinguish between one or more products and one or more unknown products in the image.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.