Abstract: A method of identifying an object captured in a video image in a multi-camera video surveillance system is disclosed. Sets of identifying information are stored in profiles, each profile being associated with one object. The disclosed method of identifying an object includes comparing identifying information extracted from images captured by the video surveillance system to one or more stored profiles. A confidence score is calculated for each comparison and used to determine a best match between the extracted set of identifying information and an object. In one embodiment, the method is used as part of a facial recognition system incorporated into a video surveillance system.

Abstract: A technique for searching for probable matches in a video surveillance system is disclosed. A new event, such as a face captured in an image set, is matched against other events in a database of events. A similarity score is generated based on the difference between the new event and other events in the database. The similarity score may be weighted by information external to the image sets. Because of limited system resources, an association between a new event and every other event in the system may not be kept. Thus, when searching for probable matches of a particular event, some events that are related to the particular event may not be initially selected. Such events may be associated with an event in a first set of events that are associated with the particular event. Therefore, a second set of events is selected that are associated with the first set of events.

Abstract: A technique is disclosed for determining when to close a group of a plurality of groups. A closed group is one to which an image set may not be added. Each group includes one or more image sets. Each image set includes one or more images of at least one object. Each group corresponds to an object that is common among images in the one or more image sets that belong to the group. Determining when to close a particular group is based, at least in part, on one or more factors, such as how many image sets are in the particular group, the length of time the particular group has been open, and data about the one or more image sets in the particular group.

Abstract: A technique is disclosed for determining when to close a group of a plurality of groups. A closed group is one to which an image set may not be added. Each group includes one or more image sets. Each image set includes one or more images of at least one object. Each group corresponds to an object that is common among images in the one or more image sets that belong to the group. Determining when to close a particular group is based, at least in part, on one or more factors, such as how many image sets are in the particular group, the length of time the particular group has been open, and data about the one or more image sets in the particular group.

Abstract: A technique is disclosed for determining a group in which to add a new image set. The new image set is captured by one or more cameras in a video surveillance system. Similarity scores are generated between the new image set and one or more image sets of a plurality of groups, wherein each group includes one or more image sets of at least one object. The new image set is added to a group based on one or more factors. Also, a technique is disclosed for determining when to close a group, wherein a closed group is one to which an image set may not be added.

Abstract: A method of identifying an object captured in a video image in a multi-camera video surveillance system is disclosed. Sets of identifying information are stored in profiles, each profile being associated with one object. The disclosed method of identifying an object includes comparing identifying information extracted from images captured by the video surveillance system to one or more stored profiles. A confidence score is calculated for each comparison and used to determine a best match between the extracted set of identifying information and an object. In one embodiment, the method is used as part of a facial recognition system incorporated into a video surveillance system.

Abstract: A method of identifying an object captured in a video image in a multi-camera video surveillance system is disclosed. Sets of identifying information are stored in profiles, each profile being associated with one object. The disclosed method of identifying an object includes comparing identifying information extracted from images captured by the video surveillance system to one or more stored profiles. A confidence score is calculated for each comparison and used to determine a best match between the extracted set of identifying information and an object. In one embodiment, the method is used as part of a facial recognition system incorporated into a video surveillance system.