Trax Technology Solutions Pte Ltd.

Aviv Eisenschtat

Yair Adato

Youval Bronicki

Alon Grubshtein

Daniel Shimon Cohen

Ziv Mhabary

Dolev Pomeranz

Itai Lishner

Yotam Michael

David M Gottlieb

Nir Hemed

Osnat Yanushevsky

Galit Peled

Yonatan Adar

Maria Kushnir

Dror Yashpe

Shlomi Dayan

Paul Yudkin

Yohai Devir

A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

Using context to update product models

A system for identifying products in a retail store is provided. The system may include a processor configured to: receive an image depicting a store shelf and a product displayed thereon; select a product model subset based on a characteristic of the store shelf determined based on analysis of the image; determine whether the product model subset is applicable to the product; and when the product model subset is applicable to the product, analyze a representation of the product depicted in the image using the product model subset, and identify the product based on the analysis of the representation of the product.

Selective usage of product models

A system for processing images captured in a retail store and differentiating between products with similar visual appearances is provided. The system may comprise at least one processor configured to receive at least one image depicting a store shelf having a product displayed thereon, analyze the at least one image to detect the product, determine that the detected product is either a first type of product or a second type of product, analyze the at least one image to determine a price associated with the detected product, determine that the detected product is of the first type of product when the determined price falls within a first price range associated with the first type of product, and determine that the detected product is of the second type of product when the determined price falls within a second price range associated with the second type of product.

Using price in visual product recognition

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Ramat Hasharon, Israel

Aviv Eisenschtat