Computer vision system and method for automatic checkout
First Claim
1. A method for a checkout process comprising:
- collecting image data across an environment;
maintaining an environmental object graph from the image data wherein the environmental object graph is a data representation of computer vision classified objects across the environment, the environmental object graph comprising at least a subset of objects having object associations;
wherein maintaining the environmental object graph comprises at least one instance of;
in a first region captured in the image data, classifying a product object and at least a shopper object,in the first region, detecting an interaction event between the product object and the shopper object, andupdating the environmental object graph whereby the product object is associated with the shopper object;
generating a checkout list from product objects associated with the shopper object in the environmental object graph.
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Abstract
A system and method for computer vision driven applications in an environment that can include collecting image data across an environment; maintaining an environmental object graph from the image data whereby maintaining the environmental object graph is an iterative process that includes: classifying objects, tracking object locations, detecting interaction events, instantiating object associations in the environmental object graph, and updating the environmental object graph by propagating change in at least one object instance across object associations; and inspecting object state for at least one object instance in the environmental object graph and executing an action associated with the object state. The system and method can be applied to automatic checkout, inventory management, and/or other system integrations.
167 Citations
35 Claims
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1. A method for a checkout process comprising:
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collecting image data across an environment; maintaining an environmental object graph from the image data wherein the environmental object graph is a data representation of computer vision classified objects across the environment, the environmental object graph comprising at least a subset of objects having object associations; wherein maintaining the environmental object graph comprises at least one instance of; in a first region captured in the image data, classifying a product object and at least a shopper object, in the first region, detecting an interaction event between the product object and the shopper object, and updating the environmental object graph whereby the product object is associated with the shopper object; generating a checkout list from product objects associated with the shopper object in the environmental object graph. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method comprising:
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collecting image data across an environment; maintaining an environmental object graph from the image data whereby maintaining the environmental object graph is an iterative process comprising; classifying objects, which comprises of classifying a first subset of objects as product objects and classifying a second subset of objects as shopper objects, storing object instances corresponding to the objects in the environmental object graph, detecting interaction events, and for a subset of detected interaction events between product object and a shopper object, updating the environmental object graph by associating the product object with the shopper object; and inspecting object state for at least one object instance in the environmental object graph and executing an action associated with the object state. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A system comprising:
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an imaging system comprised of a set of imaging devices to collect image data within an environment; a processing engine comprised of at least one processor and machine instructions that when executed by the at least one processor cause the processing engine to; maintain an environmental object graph from the image data wherein the environmental object graph is a data representation of classified objects in space and time across the environment, the environmental object graph comprising at least a subset of objects having object associations, classify objects in the image data including classifying a product objects and classifying shopper objects, store object instances that correspond to the objects in the environmental object graph, detect interaction events, and for a subset of detected interaction events between product object and a shopper object, update the environmental object graph by associating the product object with the shopper object. - View Dependent Claims (30, 31, 32, 33, 34, 35)
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Specification