Evolution Robotics, Inc.

Datalogic Adc, Inc.

Evolution Robotics Retail, Inc.

Alec Hudnut

Alex Simonini

Michael Cremean

William Tod Gross

Luis F Goncalves

Jim Ostrowski

Howard Morgan

Systems and methods for recognizing and identifying items located on the lower shelf of a shopping cart in a checkout lane of a retail store environment for the purpose of reducing or preventing loss or fraud and increasing the efficiency of a checkout process. The system includes one or more visual sensors that can take images of items and a computer system that receives the images from the one or more visual sensors and automatically identifies the items. The system can be trained to recognize the items using images taken of the items. The system relies on matching visual features from training images to match against features extracted from images taken at the checkout lane. Using the scale-invariant feature transformation (SIFT) method, for example, the system can compare the visual features of the images to the features stored in a database to find one or more matches, where the found one or more matches are used to identify the items.

Systems and methods for merchandise checkout

The invention is generally related to the systems and methods through which household appliances can provide intuitive and enhanced interactivity through visual inputs. In particular, the disclosure presents methods relating to control of a household appliance, such as a microwave or a refrigerator, via recognition of visual indicia, such as graphics, text, and the like, using a visual sensor such as a camera.

Vision-enabled household appliances

Methods and computer readable media for recognizing and identifying items located on the belt of a counter and/or in a shopping cart of a store environment for the purpose of reducing/preventing bottom-of-the-basket loss, checking out the items automatically, reducing the checkout time, preventing consumer fraud, increasing revenue and replacing a conventional UPC scanning system to enhance the checking out speed. The images of the items taken by visual sensors may be analyzed to extract features using the scale-invariant feature-transformation (SIFT) method. Then, the extracted features are compared to those of trained images stored in a database to find a set of matches. Based on the set of matches, the items are recognized and associated with one or more instructions, commands or actions without the need for personnel to visually see the items, such as by having to come out from behind a check out counter or peering over a check out counter.

Method of merchandising for checkout lanes

System and methods for merchandise checkout

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Los Angeles, CA, United States of America

Alec Hudnut