Trax Technology Solutions Pte Ltd.

Ziv Mhabary

Yair Adato

Dolev Pomeranz

Youval Bronicki

Alon Grubshtein

Daniel Shimon Cohen

Aviv Eisenschtat

Itai Lishner

Yotam Michael

Mark Cook

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 processing images captured in a retail store and automatically identifying misplaced products is provided. The system may comprise at least one processor configured to receive one or more images captured by one or more image sensors from an environment of a retail store, detect in the one or more images a first product, determine that the first product is not located in the first correct display location, cause an issuance of a user-notification associated with the first product, detect in the one or more images a second product, determine that the second product is not located in the second correct display location, and after determining that the second product is not located in the second correct display location and when the second urgency level is lower than the first urgency level, withhold issuance of a user-notification associated with the second product.

Withholding notifications due to temporary misplaced products

A system for processing images captured in a retail store and automatically identifying products displayed on shelving units, includes at least one processor configured to: receive a first image depicting a shelving unit with a plurality of products of differing product types displayed thereon and a first plurality of labels coupled to the shelving unit; receive a set of second images depicting a second plurality of labels; correlate a first label depiction of a specific label included in the first image to a second label depiction of the same specific label included in a second image; use information derived from the second label depiction to determine a type of products displayed in the first image in proximity to the specific label; and initiate an action based on the determined type of products displayed in proximity to the specific label.

Using low-resolution images to detect products and high-resolution images to detect product ID

A system for identifying perishable products in a retail store based on analysis of image data and for automatically generating suggestions relating to the identified products is provided. The system may comprise at least one processor configured to: receive a set of images depicting a plurality of perishable products displayed on at least one shelving unit in a retail store; analyze the set of images to determine information about a displayed inventory of the plurality of perishable products; obtain information about additional perishable products scheduled to be displayed on the at least one shelving unit; use the information about the displayed inventory and the information about the additional perishable products to determine at least one suggestion regarding placement of perishable products in the retail store; and provide the at least one suggestion to an entity associated with the retail store.

Managing inventory of perishable products

A system for processing images captured in a retail store is provided. The system may comprise at least one processor configured receive at least one image depicting part of at least one store shelf having a plurality of products displayed thereon, the plurality of products including a group of first products associated with a first product size and a group of second products associated with a second product size, analyze the at least one image to detect the plurality of products, identify one or more vacant spaces associated with the plurality of products, determine that by rearranging the group of second products to partially eliminate the one or more identified vacant spaces, at least one additional first product may be displayed on the at least one store shelf next to the group of first products, and provide information to a user indicative of the identified vacant spaces.

Inspecting store shelf capacity

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

A system for processing images to automatically identify occlusions in a field of view of one or more cameras in retail stores is provided. The system may comprise at least one processor configured to receive one or more images from an environment of a retail store, detect in the one or more images a first occlusion event, analyze the plurality of images to determine an indicator of a first level of urgency for resolving the first occlusion event, cause issuance of a user-notification associated with the first occlusion event, detect in the one or more images a second occlusion event, analyze the plurality of images to determine an indicator of a second level of urgency for resolving the second occlusion event, and when the second urgency level is lower than the first urgency level, withhold issuance of a user-notification associated with the second occlusion event.

Withholding alerts due to temporary shelf occlusion

Growing community of inventors

Tel Aviv, Israel

Ziv Mhabary