Yair Adato

This is a first-of-its-kind solution for identifying which training examples taught a generative model to create visual content. The process involves analyzing both the generated visual content and the training examples. The generated visual content is linked to a specific group of training examples based on their properties. Then, data records are updated to show the contribution of the specific group to the generated visual content. This recorded information helps in crediting the source of… Show more

This is a first-of-its-kind solution for identifying which training examples taught a generative model to create visual content. The process involves analyzing both the generated visual content and the training examples. The generated visual content is linked to a specific group of training examples based on their properties. Then, data records are updated to show the contribution of the specific group to the generated visual content. This recorded information helps in crediting the source of the training examples, understanding the importance of different training examples, and guiding the acquisition of additional training data. Show less

This is a solution for identifying which training examples taught a generative model to create visual content in response to a specific prompt. The process involves analyzing both the prompt and the training examples. The generated visual content is linked to a specific group of training examples based on the prompt and the properties of the training examples. Then, data records are updated to show the contribution of the specific group to the generated visual content. This recorded information… Show more

This is a solution for identifying which training examples taught a generative model to create visual content in response to a specific prompt. The process involves analyzing both the prompt and the training examples. The generated visual content is linked to a specific group of training examples based on the prompt and the properties of the training examples. Then, data records are updated to show the contribution of the specific group to the generated visual content. This recorded information helps in crediting the source of the training examples, understanding the importance of different training examples, and guiding the acquisition of additional training data. Show less

This solution determines if a specific text prompt was used to train a generative model. The process involves analyzing both the specific text prompt and data based on parameters of the generative model. It then estimates the likelihood that this prompt was used in at least one of the training examples used to create the generative model. This estimate is then provided, and may be used for various purposes, including detecting copyright infringement, verifying the authenticity of the generative… Show more

This solution determines if a specific text prompt was used to train a generative model. The process involves analyzing both the specific text prompt and data based on parameters of the generative model. It then estimates the likelihood that this prompt was used in at least one of the training examples used to create the generative model. This estimate is then provided, and may be used for various purposes, including detecting copyright infringement, verifying the authenticity of the generative model, and ensuring ethical use of data in training AI systems. Show less

Performing repeated adjustments to visual contents used in communications with different users, gauge their reactions, and then steering further adjustments to the visual contents based on those reactions. The process includes representation of visual contents as mathematical objects in a special space, and usage of mathematical optimization on these objects to select the optimal adjustment based on the reactions to the previous visual content. By iteratively improving the content, the visual… Show more

Performing repeated adjustments to visual contents used in communications with different users, gauge their reactions, and then steering further adjustments to the visual contents based on those reactions. The process includes representation of visual contents as mathematical objects in a special space, and usage of mathematical optimization on these objects to select the optimal adjustment based on the reactions to the previous visual content. By iteratively improving the content, the visual content becomes increasingly effective and appealing to users over time. Show less

The software enables a user to generate or find visual contents (like images, graphics or videos) staring from just a few. The process involves taking the user’s keywords and generates various textual prompts from them. The user has the option to tweak these prompts to better fit their vision. Once the user selects one of these textual prompts, the software then generates or retrieves multiple visual contents that align with the chosen prompt. These visuals are then displayed to the user… Show more

The software enables a user to generate or find visual contents (like images, graphics or videos) staring from just a few. The process involves taking the user’s keywords and generates various textual prompts from them. The user has the option to tweak these prompts to better fit their vision. Once the user selects one of these textual prompts, the software then generates or retrieves multiple visual contents that align with the chosen prompt. These visuals are then displayed to the user, making the process of finding or creating images and videos much more tailored to the user's specific needs and preferences. Show less

Generating a new visual content consistent with a visual brand language from on an original visual content. By analyzing the original visual content the software differentiates between brand related and brand independent visual aspects. It then modifies the non-brand elements while preserving the brand-specific aspects. This approach ensures that the newly created visual content maintains a strong connection to the brand's visual style. The end product looks like it was made for the brand… Show more

Generating a new visual content consistent with a visual brand language from on an original visual content. By analyzing the original visual content the software differentiates between brand related and brand independent visual aspects. It then modifies the non-brand elements while preserving the brand-specific aspects. This approach ensures that the newly created visual content maintains a strong connection to the brand's visual style. The end product looks like it was made for the brand, without straying too far from the original image. The generated visual content fits seamlessly within the brand's aesthetic, ready for practical applications like marketing, advertising, or social media use. This technology is particularly valuable for maintaining brand consistency across various visual media platforms and geographies. Show less

This technology transforms a single still image into a seamless, looped video clip. First, the system receives a still image. Then, using special software, it analyzes this image and creates a series of additional images that form a sequence. This sequence includes a starting image, a middle image that looks different, and an ending image that closely resembles the starting one. When these images are played in order, they form a video clip. When the video reaches the end and starts over, the… Show more

This technology transforms a single still image into a seamless, looped video clip. First, the system receives a still image. Then, using special software, it analyzes this image and creates a series of additional images that form a sequence. This sequence includes a starting image, a middle image that looks different, and an ending image that closely resembles the starting one. When these images are played in order, they form a video clip. When the video reaches the end and starts over, the transition from the last image back to the first is smooth. This is achieved through a complex process involving mathematical objects. Each image is represented as a mathematical object in a special space, and by manipulating these objects, the system can generate the sequence of images needed for the looped video. This technology automates the process of creating endless animations from a single photo. Show less

A system for acquiring images of products in a retail store is disclosed. The system may include a first housing configured for location on a retail shelving unit, and an image capture device included in the first housing and configured relative to the first housing such that an optical axis of the image capture device is directed toward an opposing retail shelving unit when the first housing is fixedly mounted on the retail shelving unit. The system may further include a second housing… Show more

A system for acquiring images of products in a retail store is disclosed. The system may include a first housing configured for location on a retail shelving unit, and an image capture device included in the first housing and configured relative to the first housing such that an optical axis of the image capture device is directed toward an opposing retail shelving unit when the first housing is fixedly mounted on the retail shelving unit. The system may further include a second housing configured for location on the retail shelving unit separate from the first housing, the second housing containing a processor configured to control the image capture device and a network interface for communicating with a remote server. The system may further include a data conduit configured to enable transfer of control signals from the processor to the image capture device.
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A system for monitoring planogram compliance on a store shelf is disclosed. The system may include a plurality of detection sensors and a processor. The processor may be configured to receive first signals from a first subset of detection sensors after a plurality of products are placed on the store shelf, and use the first signals to identify at least one pattern associated with a product type of the products. The processor may further be configured to receive from a second subset of detection… Show more

A system for monitoring planogram compliance on a store shelf is disclosed. The system may include a plurality of detection sensors and a processor. The processor may be configured to receive first signals from a first subset of detection sensors after a plurality of products are placed on the store shelf, and use the first signals to identify at least one pattern associated with a product type of the products. The processor may further be configured to receive from a second subset of detection sensors second signals indicative of no products being placed on at least one area of the store shelf, and use the second signals to determine at least one empty space on the store shelf. The processor may also be configured to determine, based on the at least one pattern and the at least one empty space, at least one aspect of planogram compliance. Show less

A system for acquiring images of products in a retail store is disclosed. The system may include at least one first housing configured for location on a retail shelving unit, and at least one image capture device included in the at least one first housing and configured relative to the at least one first housing such that an optical axis of the at least one image capture device is directed toward an opposing retail shelving unit when the at least one first housing is fixedly mounted on the… Show more

A system for acquiring images of products in a retail store is disclosed. The system may include at least one first housing configured for location on a retail shelving unit, and at least one image capture device included in the at least one first housing and configured relative to the at least one first housing such that an optical axis of the at least one image capture device is directed toward an opposing retail shelving unit when the at least one first housing is fixedly mounted on the retail shelving unit. The system may further include a second housing configured for location on the retail shelving unit separate from the at least one first housing, the second housing may contain at least one processor configured to control the at least one image capture device and also to control a network interface for communicating with a remote server. The system may also include at least one data conduit extending between the at least one first housing and the second housing, the at least one data conduit being configured to enable transfer of control signals from the at least one processor to the at least one image capture device and to enable collection of image data acquired by the at least one image capture device for transmission by the network interface. Show less

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;… Show more

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. Show less

A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order… Show more

A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period. Show less

A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the… Show more

A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the retail stores and determine durations associated with the occurrences; identify a common factor contributing to the duration of part of the occurrences of the product shortages; determine an action, associated with the at least one common factor, for potentially reducing product shortage durations of future shortages of the product type in the retail stores; and provide information associated with the identified action to an entity. Show less

A system for processing images captured in a retail store and automatically identifying a product shortage is provided. The system may comprise at least one processor configured to: access information describing a placement of products; receive image data from an image sensor; analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold; analyze a second image captured at a second time to determine that a second quantity is below the… Show more

A system for processing images captured in a retail store and automatically identifying a product shortage is provided. The system may comprise at least one processor configured to: access information describing a placement of products; receive image data from an image sensor; analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold; analyze a second image captured at a second time to determine that a second quantity is below the quantity threshold; based on the determination that the first quantity exceeds the quantity threshold, avoid initiating an unscheduled action to cause restocking the store shelf with products until a third time; analyze a third image captured at the third time to determine that a third quantity is below the quantity threshold; and based on the determination, provide information indicative of a product shortage at the store shelf. Show less

The present disclosure relates to systems and methods for identifying products in retail stores based on analysis of image data and for automatically generating performance indicators relating to the identified products. In one implementation, the system may include a processor configured to receive a first set of images depicting a first plurality of products associated with single product type displayed on a first shelving unit in a retail store; analyze the first set of images to determine… Show more

The present disclosure relates to systems and methods for identifying products in retail stores based on analysis of image data and for automatically generating performance indicators relating to the identified products. In one implementation, the system may include a processor configured to receive a first set of images depicting a first plurality of products associated with single product type displayed on a first shelving unit in a retail store; analyze the first set of images to determine first product turnover data associated with the first shelving unit; receive a second set of images depicting a second plurality of products also associated with the single product type displayed on a second shelving unit in the retail store nonadjacent to the first shelving unit; and analyze the second set of images to determine second product turnover data associated with the second shelving unit. Show less

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… Show more

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. Show less

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… Show more

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. Show less

A system for processing images captured in a retail store is provided. The system may include at least one processor configured to receive an image depicting a store shelf having at least one bottle displayed thereon and analyse the image to detect a representation in the image of the at least one bottle. The at least one bottle may have an outline design. The at least one processor is also configured to identify in the image two outline elements being associated with the outline design of the… Show more

A system for processing images captured in a retail store is provided. The system may include at least one processor configured to receive an image depicting a store shelf having at least one bottle displayed thereon and analyse the image to detect a representation in the image of the at least one bottle. The at least one bottle may have an outline design. The at least one processor is also configured to identify in the image two outline elements being associated with the outline design of the at least one bottle. Each of the two outline elements may have a specific length. The at least one processor may further be configured to determine a size of the at least one bottle based on a comparison of the lengths of the two outline elements. Show less

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… Show more

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. Show less

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… Show more

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. Show less

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… Show more

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. Show less

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… Show more

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. Show less

The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of… Show more

The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types. Show less

The present disclosure relates to systems and methods for processing images captured in a retail store and automatically addressing detected conditions within the retail store. In one implementation, the system may include a processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products; detect in the… Show more

The present disclosure relates to systems and methods for processing images captured in a retail store and automatically addressing detected conditions within the retail store. In one implementation, the system may include a processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products; detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; and access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received. Show less

Methods, devices, and computer-readable storage media for providing a user with augmented guidance to capture images of products placed on a store shelving unit, the method including using an image sensor of a mobile device to capture and display in real-time a video stream depicting a store shelving unit, augmenting the video stream with a marking identifying an area of the store shelving unit and receiving an image including an area outside the marked area. A plurality of images captured by… Show more

Methods, devices, and computer-readable storage media for providing a user with augmented guidance to capture images of products placed on a store shelving unit, the method including using an image sensor of a mobile device to capture and display in real-time a video stream depicting a store shelving unit, augmenting the video stream with a marking identifying an area of the store shelving unit and receiving an image including an area outside the marked area. A plurality of images captured by the image sensor and associated with a discontinuous first area of the store shelving unit with at least two non-overlapping regions and having image resolution higher than an image resolution of the video stream are used to mark the area of the video stream representing discontinuous first area and a second area outside the discontinuous first area. The received image overlaps the discontinuous first area and second area. Show less

This disclosure relates to systems, methods, and devices that can identify products on a shelf, and determine item descriptions and pricing from associated labels. In one embodiment, an image processing system for providing an indication about shelf label accuracy in a store is provided. The image processing system comprises at least one processor configured to receive, from a hand-held device, an image depicting products on store shelves, and associated labels coupled to the store shelves. The… Show more

This disclosure relates to systems, methods, and devices that can identify products on a shelf, and determine item descriptions and pricing from associated labels. In one embodiment, an image processing system for providing an indication about shelf label accuracy in a store is provided. The image processing system comprises at least one processor configured to receive, from a hand-held device, an image depicting products on store shelves, and associated labels coupled to the store shelves. The processor can be configured to process the image to identify at least some of the products and to access a database to determine associated product ID numbers. The processor can be further configured to determine product identifier and displayed price from the associated labels. The processor can also be configured to determine one or more product-label mismatches related to incorrect product placement on the shelf and to provide electronic notification of the mismatches. Show less

The present disclosure provides a method of image processing comprising: obtaining by an imaging device a low resolution version and a high resolution version of a retail image, the high resolution version of the retail image being a temporary file to be erased automatically after a predetermined time period; transmitting to a server the low resolution version of the retail image; upon receipt of a request from the server, the request including data representative of a contour of an… Show more

The present disclosure provides a method of image processing comprising: obtaining by an imaging device a low resolution version and a high resolution version of a retail image, the high resolution version of the retail image being a temporary file to be erased automatically after a predetermined time period; transmitting to a server the low resolution version of the retail image; upon receipt of a request from the server, the request including data representative of a contour of an unidentified item in the low resolution version of the retail image, cropping a high resolution item image from the high resolution version of the retail image, the high resolution item image corresponding to the contour of the unidentified item; and transmitting the high resolution item image to the server thereby enabling updating an item database. Show less