System and method for providing surveillance data
First Claim
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1. A system for providing surveillance data comprising:
- a pattern learner, implemented by at least one processor, configured to learn a first time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the first time-based data pattern; and
an event detector, implemented by the at least one processor, configured to detect at least one event by comparing the event model with a second time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone,wherein the first time-based data pattern represents a time-based variation in the at least one of the image data and the sound data, and the event detector is configured to detect the at least one event in response to determining that at least one of the first image data and the first sound data deviates, out of a preset error range, from the time-based variation of the first time-based data pattern.
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Abstract
A system and method for providing surveillance data are provided. The system includes: a pattern learner configured to learn a time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the time-based data pattern; and an event detector configured to detect at least one event by comparing the event model with a time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone.
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Citations
21 Claims
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1. A system for providing surveillance data comprising:
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a pattern learner, implemented by at least one processor, configured to learn a first time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the first time-based data pattern; and an event detector, implemented by the at least one processor, configured to detect at least one event by comparing the event model with a second time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone, wherein the first time-based data pattern represents a time-based variation in the at least one of the image data and the sound data, and the event detector is configured to detect the at least one event in response to determining that at least one of the first image data and the first sound data deviates, out of a preset error range, from the time-based variation of the first time-based data pattern. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of providing surveillance data, the method comprising:
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learning a first time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the first time-based data pattern; and detecting at least one event by comparing the event model with a second time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone, wherein the first time-based data pattern represents a time-based variation in the at least one of the image data and the sound data, and the detecting the at least one event comprises detecting the at least one event in response to determining that at least one of the first image data and the first sound data deviates, out of a preset error range, from the time-based variation of the first time-based data pattern. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A system for providing surveillance data comprising:
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a pattern learner, implemented by at least one processor, configured to learn a first time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the first time-based data pattern; and an event detector, implemented by the at least one processor, configured to detect at least one event by comparing the event model with a second time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone, wherein the pattern learner is configured to obtain a statistical data value with respect to at least one of at least one object detected from the one or more images and at least one sound level from the sound, and the first time-based data pattern corresponds to a time-based variation in the statistical data value.
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Specification