Tandent Vision Science, Inc.

Videomining Corporation

Youngrock R Yoon

Rajeev Sharma

Casey Arthur Smith

Joonhwa Shin

Donghun Kim

Richard Mark Friedhoff

Bruce Allen Maxwell

Andrew Neil Stein

Kshitiz Garg

Neil Alldrin

Kristin Jean Dana

Timothy King Rodgers, Jr

Matthias M De Haan

Besma Roui Abidi

A method and system for creating an anonymous shopper panel based on multi-modal sensor data fusion. The anonymous shopper panel can serve as the same traditional shopper panel who reports their household information, such as household size, income level, demographics, etc., and their purchase history, yet without any voluntary participation. A configuration of vision sensors and mobile access points can be used to detect and track shoppers as they travel a retail environment. Fusion of those modalities can be used to form a trajectory. The trajectory data can then be associated with Point of Sale data to form a full set of shopper behavior data. Shopper behavior data for a particular visit can then be compared to data from previous shoppers' visits to determine if the shopper is a revisiting shopper. The shopper's data can then be aggregated for multiple visits to the retail location. The aggregated shopper data can be filtered using application-specific criteria to create an anonymous shopper panel.

Method and system for creating anonymous shopper panel using multi-modal sensor fusion

A method and system for associating a mobile device carried by a shopper with Point-of-Sale (PoS) data from that shopper's transaction at a retail location. Specifically, the association can utilize face data that was associated with the mobile device to match face data that was generated by association with PoS data. The association with a mobile device can also include the calculation of a mobile trajectory to enable the generation of a shopper profile including shopper behavior. The mobile to PoS association can include tracking of the mobile device throughout a retail location to form a trajectory. The association of a face to a mobile device can utilize the device's MAC address and repeat visit analysis to determine a match. The association of a face to PoS data can utilize the aligning of event time series based on a dynamic time disparity to match checkout events with PoS events.

Association of mobile device to retail transaction

A method and system for cross-channel shopper behavior analysis. Tracking individual shopper behavior across many retail locations (i.e., across multiple channels) can be extremely valuable for product manufacturers and retails. A configuration of vision sensors and mobile access points can be used to detect and track shoppers as they travel a retail environment, forming a trajectory. The trajectory data can then be associated with Point of Sale data to form a full set of shopper behavior data. The shopper's data can then be aggregated for multiple visits to many retail locations in a geographic area. The aggregated shopper data can be filtered using application-specific criteria for further analysis.

Cross-channel in-store shopper behavior analysis

A method and system for associating an image of a face of at least a person with Point-of-Sale (PoS) data by aligning a first event time series with a second event time series based on a dynamic time disparity. An exemplary embodiment can generate an event time series containing facial recognition data for a person or persons during the PoS transaction process. These data can form a vision-based checkout event time series. An embodiment can also collect PoS transaction data from the retail checkout system, using timestamp information to create a second event time series. As there may be a time disparity between the time series, they can then be aligned in order to match events from one time series to the other. Faces identified in checkout events in the first time series can be registered to PoS events and the results stored in a database.

Association of unique person to point-of-sale transaction data

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of, at a computer system, receiving an image recorded at and transmitted from a remote source, at the computer system, processing the transmitted image, for segregation of the transmitted image into a corresponding intrinsic image and, at the computer system, processing the corresponding intrinsic image to perform a preselected task, for a result. As a further feature of the first exemplary embodiment of the present invention, the remote source comprises a cell phone or remote computer system.

Method and system for processing an image received from a remote source

An automated, computerized method is provided for processing an image. The method includes the steps of providing an image file depicting an image, in a computer memory, identifying a dominant region of single reflectance in the image and segregating the image into intrinsic images as a function of the dominant region of single reflectance.

Method and system for generating intrinsic images using a single reflectance technique

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, assembling a feature vector for the image file, the feature vector containing information regarding a likelihood that a selected pair of regions of the image file are of a same intrinsic characteristic, for example, a same texture, providing a classifier derived from a computer learning technique, computing a classification score for the selected pair of regions of the image file, as a function of the feature vector and the classifier and classifying the regions as being of the same intrinsic characteristic, as a function of the classification score.

Image segregation system with method for handling textures

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, identifying a dominant region of single reflectance in the image and segregating the image into intrinsic images as a function of the dominant region of single reflectance.

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Knoxville, TN, United States of America

Youngrock R Yoon