Apparatus and method for measuring audience data from image stream using dynamically-configurable hardware architecture
First Claim
1. An apparatus for measuring audience data from at least an image stream using dynamically-configurable hardware architecture, comprising:
- a) means for aggregating computational modules using a directed graph,wherein every vertex of the graph represents a computational module that implements a classifier or a computational component that constitutes a classifier, and every edge of the graph between a first computational module and a second computational module represents a decision of whether or not the processing goes from the first computational model to the second computational module and any data that need to be passed from the first computational module and the second computational module,b) means for determining an audience measurement hardware architecture and the computation that the architecture carries out, based on the presence and absence of the edges between the vertices and the kind of computation that is represented by the edge in the graphical model,c) a supervising control to change the hardware configuration in executing the computational modules in the system,wherein the supervising control monitors the external or internal environment to make a decision whether or not it is necessary to reconfigure the system to adjust to the changes in environment,wherein the supervising control then makes a decision about how to change the hardware configurations to adapt to the given environment, andwherein the audience data comprises the behavioral attributes and demographics of the audience per node.
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Abstract
The present invention is an embedded audience measurement platform, which is called HAM. The HAM includes hardware, apparatus, and method for measuring audience data from image stream using dynamically-configurable hardware architecture. The HAM provides an end-to-end solution for audience measurement, wherein reconfigurable computational modules are used as engines per node to power the complete solution implemented in a flexible hardware architecture. The HAM is also a complete system for broad audience measurement, which has various components built into the system. Examples of the components comprise demographics classification, gaze estimation, emotion recognition, behavior analysis, and impression measurement.
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Citations
20 Claims
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1. An apparatus for measuring audience data from at least an image stream using dynamically-configurable hardware architecture, comprising:
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a) means for aggregating computational modules using a directed graph, wherein every vertex of the graph represents a computational module that implements a classifier or a computational component that constitutes a classifier, and every edge of the graph between a first computational module and a second computational module represents a decision of whether or not the processing goes from the first computational model to the second computational module and any data that need to be passed from the first computational module and the second computational module, b) means for determining an audience measurement hardware architecture and the computation that the architecture carries out, based on the presence and absence of the edges between the vertices and the kind of computation that is represented by the edge in the graphical model, c) a supervising control to change the hardware configuration in executing the computational modules in the system, wherein the supervising control monitors the external or internal environment to make a decision whether or not it is necessary to reconfigure the system to adjust to the changes in environment, wherein the supervising control then makes a decision about how to change the hardware configurations to adapt to the given environment, and wherein the audience data comprises the behavioral attributes and demographics of the audience per node. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A method for measuring audience data from at least an image stream using a dynamically-configurable hardware architecture, comprising the steps of:
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a) aggregating computational modules using a directed graph, wherein every vertex of the graph represents a computational module that implements a classifier or a computational component that constitutes a classifier, and every edge of the graph between a first computational module and a second computational module represents a decision of whether or not the processing goes from the first computational module to the second computational module and any data that need to be passed from the first computational module and the second computational module, b) determining an audience measurement hardware architecture and the computation that the architecture carries out, based on the presence and absence of the edges between the vertices and the kind of the computation that is represented by the edge in the graphical model, c) utilizing a supervising control to change the hardware configuration in executing the computational modules in the system, wherein the supervising control monitors the external or internal environment to make a decision of whether or not it is necessary to reconfigure the system to adjust to the changes in environment, wherein the supervising control then makes a decision about how to change the hardware configurations to adapt to the given environment, and wherein the audience data comprises behavioral attributes and demographics of the audience per node. - View Dependent Claims (20)
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Specification