Optimizing video stream processing
First Claim
1. A method, comprising:
- obtaining by a processor streams of video and transaction data captured from each of a plurality of different checkout lanes;
combining by the processor the streams of video and transaction data for each respective one of the different checkout lanes into individual transaction units that each comprise transaction video corresponding to a set of items purchased by a single customer at one of the different checkout lanes in a single span of time;
determining processing priority by the processor for each transaction unit of the individual transaction units as a function of a lane priority value of a respective one of the different checkout lanes that the transaction unit video and transaction data is captured from, wherein each of the different checkout lanes have a different lane priority value, and as a function of a transaction unit type priority value of a type of transaction unit indicated by the transaction data of the transaction unit, wherein the transaction unit type is selected from a plurality of different transaction unit types that each have a different transaction unit type priority value; and
processing by the processor a high priority fraction of a total of the individual transaction units based on the determined processing priority for each of the transaction units to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed transaction units.
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Accused Products
Abstract
The present invention involves implementation of an intelligent switching program, whereby the processing power required to monitor check-out stations is considerably reduced. The present invention monitors a subset of check-out stations at any given time, instead of monitoring all check-out stations at all times. The subset of check-out stations is determined dynamically according to, but not limited to, cashier records, input parameters from the user, current lane activity, past lane activity, time of day, etc. Statistical models (e.g., effective population sampling and/or population hypothesis tests) are developed along these lines that guide the lane selection process, whereby increases in the false-negative rate due to failure to monitor particular lanes when events of interest occur are controlled. By monitoring fewer check-out stations, while maintaining target performance accuracy, the amount of data that end users must deal with is significantly reduced.
44 Citations
22 Claims
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1. A method, comprising:
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obtaining by a processor streams of video and transaction data captured from each of a plurality of different checkout lanes; combining by the processor the streams of video and transaction data for each respective one of the different checkout lanes into individual transaction units that each comprise transaction video corresponding to a set of items purchased by a single customer at one of the different checkout lanes in a single span of time; determining processing priority by the processor for each transaction unit of the individual transaction units as a function of a lane priority value of a respective one of the different checkout lanes that the transaction unit video and transaction data is captured from, wherein each of the different checkout lanes have a different lane priority value, and as a function of a transaction unit type priority value of a type of transaction unit indicated by the transaction data of the transaction unit, wherein the transaction unit type is selected from a plurality of different transaction unit types that each have a different transaction unit type priority value; and processing by the processor a high priority fraction of a total of the individual transaction units based on the determined processing priority for each of the transaction units to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed transaction units. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for providing a service for automatically detecting irregular activities indicated by the transaction unit video and transaction data, the method comprising:
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integrating computer-readable program code into a computer system comprising a processor, a computer readable memory and a computer readable tangible storage device, wherein the computer readable program code is embodied on the computer readable tangible storage device and comprises instructions that, when executed by the processor via the computer readable memory, cause the processor to; obtain streams of video and transaction data captured from each of a plurality of different checkout lanes; combine the streams of video and transaction data for each respective one of the different checkout lanes into individual transaction units that each comprise transaction video corresponding to a set of items purchased by a single customer at one of the different checkout lanes in a single span of time; determine processing priority for each transaction unit of the individual transaction units as a function of a lane priority value of a respective one of the different checkout lanes that the transaction unit video and transaction data is captured from, wherein each of the different checkout lanes have a different lane priority value, and as a function of a transaction unit type priority value of a type of transaction unit indicated by the transaction data of the transaction unit, wherein the transaction unit type is selected from a plurality of different transaction unit types that each have a different transaction unit type priority value; and process a high priority fraction of a total of the individual transaction units based on the determined processing priority for each of the transaction units to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed transaction units. - View Dependent Claims (12, 13, 14)
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15. A system, comprising:
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a processor in communication with a computer readable memory and a tangible computer-readable storage device; wherein the processor, when executing program instructions stored on the tangible computer-readable storage device via the computer readable memory; obtains streams of video and transaction data captured from each of a plurality of different checkout lanes; combines the streams of video and transaction data for each respective one of the different checkout lanes into individual transaction units that each comprise transaction video corresponding to a set of items purchased by a single customer at one of the different checkout lanes in a single span of time; determines processing priority for each transaction unit of the individual transaction units as a function of a lane priority value of a respective one of the different checkout lanes that the transaction unit video and transaction data is captured from, wherein each of the different checkout lanes have a different lane priority value, and as a function of a transaction unit type priority value of a type of transaction unit indicated by the transaction data of the transaction unit, wherein the transaction unit type is selected from a plurality of different transaction unit types that each have a different transaction unit type priority value; and processes a high priority fraction of a total of the individual transaction units based on the determined processing priority for each of the transaction units to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed transaction units. - View Dependent Claims (16, 17, 18)
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19. An article of manufacture, comprising:
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a computer readable tangible storage device having computer readable program code embodied therewith, the computer readable program code comprising instructions that, when executed by a computer processor, cause the computer processor to; obtain streams of video and transaction data captured from each of a plurality of different checkout lanes; combine the streams of video and transaction data for each respective one of the different checkout lanes into individual transaction units that each comprise transaction video corresponding to a set of items purchased by a single customer at one of the different checkout lanes in a single span of time; determine processing priority for each transaction unit of the individual transaction units as a function of a lane priority value of a respective one of the different checkout lanes that the transaction unit video and transaction data is captured from, wherein each of the different checkout lanes have a different lane priority value, and as a function of a transaction unit type priority value of a type of transaction unit indicated by the transaction data of the transaction unit, wherein the transaction unit type is selected from a plurality of different transaction unit types that each have a different transaction unit type priority value; and process a high priority fraction of a total of the individual transaction units based on the determined processing priority for each of the transaction units to automatically detect irregular activities indicated by the transaction unit video and the transaction data of the processed transaction units. - View Dependent Claims (20, 21, 22)
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Specification