Video data storage, search, and retrieval using meta-data and attribute data in a video surveillance system
First Claim
1. A method of storing video data, associated meta-data, and associated attribute weights from a video surveillance system, the method comprising:
- capturing video data from one or more surveillance cameras;
generating meta-data by performing video analysis on the video data from the surveillance cameras, the meta-data representing events detected in the video data;
determining attribute weights, representing information about the relevance of the meta-data;
generating intersections of two or more subsets of the meta-data to generate intersection meta-data;
determining attribute weights associated with the intersection meta-data by multiplying the attribute weights for each subset of meta-data;
generating unions of two or more subsets of the meta-data to generate union meta-data;
determining attribute weights associated with the union meta-data by adding the attribute weights for each subset of meta-data and subtracting a multiple of the attribute weights of each subset of meta-data;
changing the attribute weights based on external events by computing future attribute weights from past attribute weights by composing past attribute weights with external event weights;
storing the video data in a video storage area;
storing the meta-data, indexed by date and time stamp to the video data, in a meta-data storage area; and
storing the attribute weights in an attribute storage area,wherein attribute weights for the intersection meta-data is calculated using the equation;
W(M1∩
M2)=W(M1)·
W(M2),wherein attribute weights for the union meta-data is calculated using the equation;
W(M1∪
M2)=W(M1)+W(M2)−
W(M1)·
W(M2), andwherein M1 and M2 are two subsets of meta-data, W(M1) is an attribute weight associated with subset M1, W(M2) is an attribute weight associated with subset M2, W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2, and W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2.
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0 Petitions
Accused Products
Abstract
One embodiment is a method of storing video data from a video surveillance system having one or more cameras. Video data is captured from one or more surveillance cameras. Meta-data is automatically generated by performing video analysis on the captured video data from the surveillance cameras. A human operator may manually enter additional meta-data. Attribute data and associated weights, representing information about the relevance of the meta-data, is received. The video data is stored in a hierarchical video storage area; the meta-data, indexed by date and time stamp to the video data, is stored in a meta-data storage area; and the attribute data is stored in an attribute storage area. One or more alerts may be issued based on the past and present meta-data. The video data is secured by encrypting and storing the video data remotely, and audit trails are generated about who and when viewed the video data.
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Citations
22 Claims
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1. A method of storing video data, associated meta-data, and associated attribute weights from a video surveillance system, the method comprising:
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capturing video data from one or more surveillance cameras; generating meta-data by performing video analysis on the video data from the surveillance cameras, the meta-data representing events detected in the video data; determining attribute weights, representing information about the relevance of the meta-data; generating intersections of two or more subsets of the meta-data to generate intersection meta-data; determining attribute weights associated with the intersection meta-data by multiplying the attribute weights for each subset of meta-data; generating unions of two or more subsets of the meta-data to generate union meta-data; determining attribute weights associated with the union meta-data by adding the attribute weights for each subset of meta-data and subtracting a multiple of the attribute weights of each subset of meta-data; changing the attribute weights based on external events by computing future attribute weights from past attribute weights by composing past attribute weights with external event weights; storing the video data in a video storage area; storing the meta-data, indexed by date and time stamp to the video data, in a meta-data storage area; and storing the attribute weights in an attribute storage area, wherein attribute weights for the intersection meta-data is calculated using the equation;
W(M1∩
M2)=W(M1)·
W(M2),wherein attribute weights for the union meta-data is calculated using the equation;
W(M1∪
M2)=W(M1)+W(M2)−
W(M1)·
W(M2), andwherein M1 and M2 are two subsets of meta-data, W(M1) is an attribute weight associated with subset M1, W(M2) is an attribute weight associated with subset M2, W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2, and W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A video surveillance system, comprising:
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one or more surveillance cameras for capturing video data; one or more video storage areas for storing video data; a meta-data storage area for storing meta-data; an attribute storage area for storing attribute weights; and a processor, the processor coupled to the video storage areas, the meta-data storage area, and the attribute storage area, the processor adapted to execute program code to; capture video data from one or more surveillance cameras; generate meta-data by performing video analysis on the video data from the surveillance cameras, the meta-data representing events detected in the video data; determine attribute weights, representing information about the relevance of the meta-data; generate intersections of two or more subsets of the meta-data to generate intersection meta-data; determine attribute weights associated with the intersection meta-data by multiplying the attribute weights for each subset of meta-data; generate unions of two or more subsets of the meta-data to generate union meta-data; determine attribute weights associated with the union meta-data by adding the attribute weights for each subset of meta-data and subtracting a multiple of the attribute weights of each subset of meta-data; change the attribute weights based on external events by computing future attribute weights from past attribute weights by composing past attribute weights with external event weights; store the video data in a video storage area; store the meta-data, indexed by date and time stamp to the video data, in a meta-data storage area; and store the attribute weights in an attribute storage area, wherein attribute weights for the intersection meta-data is calculated using the equation;
W(M1∩
M2)=W(M1)·
W(M2),wherein attribute weights for the union meta-data is calculated using the equation;
W(M1∪
M2)=W(M1)+W(M2)−
W(M1)·
W(M2), andwherein M1 and M2 are two subsets of meta-data, W(M1) is an attribute weight associated with subset M1, W(M2) is an attribute weight associated with subset M2, W(M1∩
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2, and W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A method of searching and retrieving video data from a video surveillance system, the method comprising:
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entering a search criteria; searching meta-data associated with the video data, the meta-data generated by one or more video detection components and indexed to the video data; retrieving meta-data matching the search criteria from a meta-data module; retrieving video data indexed by the meta-data from a video storage module; and retrieving attribute weights associated with the meta-data, the attribute weights representing reliability of the meta-data, wherein attribute weights for intersection meta-data of two sub-sets of meta-data is calculated using the equation;
W(M1∩
M2)=W(M1)·
W(M2),wherein attribute weights for union meta-data of two sub-sets of meta-data is calculated using the equation W(M1∪
M2)=W(M1)+W(M2)−
W(M1)·
W(M2),wherein M1 and M2 are two subsets of meta-data, W(M1) is an attribute weight associated with subset M1, W(M2) is an attribute weight associated with subset M2, W(M1∩
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2, and W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2. - View Dependent Claims (18, 19)
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20. An apparatus for storing video data, associated meta-data, and associated attribute weights from a video surveillance system, the apparatus comprising:
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means for capturing video data from one or more surveillance cameras; means for generating meta-data by performing video analysis on the video data from the surveillance cameras, the meta-data representing events detected in the video data; means for determining attribute weights, representing information about the relevance of the meta-data; means for generating intersections of two or more subsets of the meta-data to generate intersection meta-data; means for determining attribute weights associated with the intersection meta-data by multiplying the attribute weights for each subset of meta-data; means for generating unions of two or more subsets of the meta-data to generate union meta-data; means for determining attribute weights associated with the union meta-data by adding the attribute weights for each subset of meta-data and subtracting a multiple of the attribute weights of each subset of meta-data; means for changing the attribute weights based on external events by computing future attribute weights from past attribute weights by composing past attribute weights with external event weights; means for storing the video data in a video storage area; means for storing the meta-data, indexed by date and time stamp to the video data, in a meta-data storage area; and means for storing the attribute weights in an attribute storage area, wherein attribute weights for the intersection meta-data is calculated using the equation;
W(M1∩
M2)=W(M1)·
W(M2),wherein attribute weights for the union meta-data is calculated using the equation;
W(M1∪
M2)=W(M1)+W(M2)−
W(M1)·
W(M2), andwherein M1 and M2 are two subsets of meta-data, W(M1) is an attribute weight associated with subset M1, W(M2) is an attribute weight associated with subset M2, W(Mi∩
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2, and W(M1∪
M2) is a calculated attribute weight associated with the intersection meta-data of subset M1 and subset M2. - View Dependent Claims (21, 22)
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Specification