Abstract: Techniques for implementing voice-based liveness verification are provided. In one embodiment, a computing device can present a series of challenge prompts to a user being authenticated, where each challenge prompt corresponds to a request to utter a liveness passphrase that is randomly selected from a set of liveness passphrases that have been previously enrolled by an enrolled user of the computing device. The computing device can then receive utterances from the user in response to the series of challenge prompts and, if each utterance matches its corresponding enrolled liveness passphrase, can conclude that the user is a live subject.

Abstract: Techniques for implementing voice-based liveness verification are provided. In one embodiment, a computing device can present a series of challenge prompts to a user being authenticated, where each challenge prompt corresponds to a request to utter a liveness passphrase that is randomly selected from a set of liveness passphrases that have been previously enrolled by an enrolled user of the computing device. The computing device can then receive utterances from the user in response to the series of challenge prompts and, if each utterance matches its corresponding enrolled liveness passphrase, can conclude that the user is a live subject.

Abstract: A method and apparatus for storing video data is provided. Video data, that comprises a series of frames, is received. Information about changes that are detected in the series of frames is generated. The information is aggregated to generate a plurality of video data change records. Each video data change record corresponds to a plurality of frames and includes change information that indicates changes that were detected relative to the corresponding plurality of frames. Events of interest that satisfy specified search criteria are searched for by comparing the specified search criteria against change information in one or more of the plurality of video data change records.

Abstract: A method and apparatus is described for specifying regions of interest within a two-dimensional view of visual information that comprises a series of frames. Visual changes that occur in the view are stored. A user enters search criteria that specify at least one first region of interest within the view and a visual change. A visual change may include a change in pixel values or a detection of motion of one or more objects within the view. The first search criteria are compared against the stored visual changes to identify a sequence of frames in which the specified visual change occurred within the first region of interest. The search criteria may specify multiple regions of interest, each with one or more types of visual changes. If a motion is specified, then a direction, speed, and behavior of a moving object may also be specified.

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 method of displaying video surveillance system information is disclosed. Video clips associated with events are represented by event cards. The event cards include frames selected from the video clips associated with the events. Event cards include metadata, and can be annotated. Display of overlapping event cards causes a compressed event card to be displayed. Selection of a compressed event card dynamically expands the compressed event card to display a paneled event card.

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 pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.

Abstract: A method of managing video data storage in a video surveillance system is disclosed. The disclosed methods extend the amount of calendar time for which video and image data can be stored on a storage device. The disclosed methods apply decision criteria, such as rules, configuration data and preferences, to support intelligent automatic reduction of stored surveillance data such that images and video data of most interest are maintained while less important data is deleted, compressed or archived.

Abstract: A pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.

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.