Video data storage, search, and retrieval using meta-data and attribute data in a video surveillance system

A video surveillance system, comprising:

• 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), and
• 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.

A method of searching and retrieving video data from a video surveillance system, the method comprising:

• 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.

An apparatus for storing video data, associated meta-data, and associated attribute weights from a video surveillance system, the apparatus comprising:

• 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), and
• 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(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.