Videomining Corporation

Varij Saurabh

Rajeev Sharma

Namsoon Jung

Priya Baboo

Hankyu Moon

Satish Mummareddy

Jeff Hershey

The present invention is a method and system for evaluating relative effectiveness of content in a digital signage network, using a series of measurements to compare and evaluate different contents. The measurements are performed on a plurality of input images of the people captured by a plurality of means for capturing images in the vicinity of at least a digital signage. The present invention is a content rating system based on how the audience responds to the digital content in the intended context of digital media network in-store or in other public viewing areas. The present invention allows the measurement of the response to the content for different segments, further allowing for better planning of the content and optimizing the advertising dollars.

Method and system for evaluating content for digital displays by measuring viewer responses by demographic segments

The present invention is a method and system for capturing a dataset over time that represents the response of shoppers to a set of marketing and merchandising stimuli or 'elements'. The response includes exposure metrics, engagement metrics and conversion metrics for different shopper segments. The shopper segments may be defined by demographics such as gender, age and ethnicity or by the type of trip, such as a quick trip or a fill-up trip. The system comprises a plurality of means for capturing images, such as cameras, covering the area of interest in the vicinity of the marketing or merchandising element. The method comprises automated and semi-automated analysis of the video to extract the shopper behavior and demographics data for computing the defined metrics. The captured data can be further combined with information such a promotions and advertisement outside the store to further enhance the applications of the data collected in-store from the invention. The captured shopper data can be used for many applications such as comparison of the effectiveness of different marketing elements or the relative effectiveness of different types of promotions, variation of the relative effectiveness of different marketing elements over time or differences between the relative effectiveness of a marketing element for different demographic segments.

Method and system for collecting shopper response data tied to marketing and merchandising elements

The present invention is a system and method for measuring effectiveness of a marketing campaign on digital signage on many different signage networks, by measuring the efficiency of the campaign at reaching targeted audience and the effectiveness of conveying the message. This invention provides a solution to the challenges created by wide variety of measurements and lack of accuracy. By using automated audience measurement, the current invention is able to collect, large, statistically significant data for analysis. Non-intrusive, computer based measurement also ensure that the data is free from any biases. The media content rating system will provide a quantitative measure of how many people did the campaign reach and what effect did it have. The data will be available at the aggregate level, at network level and down to the screen level.

Method and system for measuring effectiveness of a marketing campaign on digital signage

The present invention is a method and system for rating in-store media elements based on the measurement for behavior patterns and demographics of the audience in the vicinity of the media element, where a plurality of input images of the audience are captured by at least a means for capturing images in the vicinity of the media element. The input images are processed by automated video analytic algorithms in order to measure the behavior patterns and demographics of each person in the audience tied to the media element. The measurements for the behavior patterns and demographics of the audience from the target media elements are aggregated. A set of ratings for the media element is calculated based on the measurements. The measured media elements are sampled, and the audience measurement for the sample is extrapolated to other media elements for in-store locations or for a group of stores. The ratings are converted into a standardized output. The standardized output facilitates comparisons among a plurality of media elements. The rating can be used to plan media types in the media element for reaching targeted demographics.

Method and system for rating in-store media elements

The present invention is a system, method, and apparatus for determining the impact of crowding on retail performance based on a measurement for behavior patterns of people in a store area. The present invention captures a plurality of input images of the people by at least a means for capturing images, such as cameras, in the store area. In the captured plurality of input images, each person's shopping path is detected by a video analytics-based tracking algorithm. A subset of the people is identified as a crowd in the store area. In relation to the crowd, the behavior patterns of the target person are measured. After aggregating the measurements for the behavior patterns over a predefined window of time, the present invention can calculate a crowd index and a crowd impact index for the store area based on the measurements. A crowd index shows the level of crowd density in the store area caused by a crowd, including traffic count of the crowd in the store area. A crowd impact index comprises a traffic count of the target people who make trips to the store area and a shopping time index, such as average shopping time changes of the target people, in relation to a crowd in the measured store area.

Method and system for determining the impact of crowding on retail performance

The present invention is a method and system for producing a set of ratings for out-of-home media based on the measurement of behavior patterns and demographics of the people in a digital media network. The present invention captures a plurality of input images of the people in the vicinity of sampled out-of-home media in a digital media network by a plurality of means for capturing images, and tracks each person. The present invention processes the plurality of input images in order to analyze the behavior and demographics of the people. The present invention aggregates the measurements for the behavior patterns and demographics of the people, analyzes the data, and extracts characteristic information based on the estimated parameters from the aggregated measurements. Finally, the present invention calculates a set of ratings based on the characteristic information. The plurality of computer vision technologies can comprise face detection, person tracking, body parts detection, and demographic classification of the people, on the captured visual information of the people in the vicinity of the out-of-home media.

Method and system for rating of out-of-home digital media network based on automatic measurement

The present invention is a method and system for measuring a set of shopper behavior metrics that represent the strength of a product category or a group of categories in the performance of a store area. A set of rating parameters are defined in order to provide a unified and standardized rating system. The rating system represents the effectiveness of the product category in a store area. The metrics are defined in a manner that is normalized so that they can be used across different types of product categories. The datasets are measured per category or group of categories over time to identify how the strength has varied over time, and to monitor trends in the category performance. The measured datasets are further analyzed based on various demographic groups and behavior segments. The analysis facilitates a better understanding of the strength of the category for different shopper segments, which in turn can be applied for developing better store area optimization strategies.

Method and system for rating the role of a product category in the performance of a store area

The present invention is a system and method for determining the hierarchical purchase decision process of consumers in front of a product category. The decision path of consumers is obtained by combining behavior data with the category layout and transaction data based on observed actual in-store purchase behavior using a set of video cameras and software for extracting sequence and timing of each consumer's decision process. A hierarchical decision tree structure comprises nodes and edges, wherein a node represents the state-of-mind of the consumer, the number of nodes is predefined, and an edge represents the transition of the decision. The decisions for each product group are captured down to the product attribute level and analyzed by demographic group. The outcome provides relative importance of each product attribute in the purchase decision process, and helps retailers and manufacturers to evaluate the layout of the category and customize it for key segment.

Method and system for building a consumer decision tree in a hierarchical decision tree structure based on in-store behavior analysis

The present invention is a system and framework for augmenting any retail transaction system with information about the involved customers. This invention provides a method to combine the transaction data records and a customer or a group of customers with the automatically extracted demographic features (e.g., gender, age, and ethnicity), shopping group information, and behavioral information using computer vision algorithms. First, the system detects faces from face view, tracks them individually, and estimates poses of each of the tracked faces to normalize. These facial images are processed by the demographics classification module to determine and record the demographics feature vector. The system detects and tracks customers to analyze the dynamic behavior of the tracked customers so that their shopping group membership and checkout behavior can be recognized. Then the instances of faces and the instances of bodies can be matched and combined. Finally, the transaction data from the transaction data and the demographics, group, and checkout behavior data that belong to the same person or the same group of people are combined.

Method for augmenting transaction data with visually extracted demographics of people using computer vision

The present invention is a method and system for selectively executing content on a display based on the automatic recognition of predefined characteristics, including visually perceptible attributes, such as the demographic profile of people identified automatically using a sequence of image frames from a video stream. The present invention detects the images of the individual or the people from captured images. The present invention automatically extracts visually perceptible attributes, including demographic information, local behavior analysis, and emotional status, of the individual or the people from the images in real time. The visually perceptible attributes further comprise height, skin color, hair color, the number of people in the scene, time spent by the people, and whether a person looked at the display. A targeted media is selected from a set of media pools, according to the automatically-extracted, visually perceptible attributes and the feedback from the people.

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State College, PA, United States of America

Varij Saurabh