Abstract: Embodiments of the disclosure provide for systems and methods for creating metadata associated with a video data. The metadata can include data about objects viewed within a video scene and/or events that occur within the video scene. Some embodiments allow users to search for specific objects and/or events by searching the recorded metadata. In some embodiments, metadata is created by receiving a video frame and developing a background model for the video frame. Foreground object(s) can then be identified in the video frame using the background model. Once these objects are identified they can be classified and/or an event associated with the foreground object may be detected. The event and the classification of the foreground object can then be recorded as metadata.

Abstract: Embodiments of the disclosure provide for systems and methods for creating metadata associated with a video data. The metadata can include data about objects viewed within a video scene and/or events that occur within the video scene. Some embodiments allow users to search for specific objects and/or events by searching the recorded metadata. In some embodiments, metadata is created by receiving a video frame and developing a background model for the video frame. Foreground object(s) can then be identified in the video frame using the background model. Once these objects are identified they can be classified and/or an event associated with the foreground object may be detected. The event and the classification of the foreground object can then be recorded as metadata.

Abstract: Techniques are discussed for providing mechanisms for coding and transmitting high definition video, e.g., over low bandwidth connections. In particular, foreground-objects are identified as distinct from the background of a scene represented in a plurality of video frames received from a video source, such as a camera. In identifying foreground-objects, semantically significant and semantically insignificant movement (e.g., repetitive versus non-repetitive movement) is differentiated. Processing of the foreground-objects and background proceed at different update rates or frequencies.

Abstract: Systems and methods of sorting electronic color images of objects are provided. One method includes receiving an input representation of an object, the representation including pixels defined in a first color space, converting the input image into a second color space, determining a query feature vector including multiple parameters associated with color of the input representation, the query feature vector parameters including at least a first parameter of the first color space and at least a first parameter of the second color space and comparing the query feature vector to multiple candidate feature vectors. Each candidate feature vector includes multiple parameters associated with color of multiple stored candidate images, the candidate feature vector parameters including at least the first parameter from the first color space and at least the first parameter from the second color space.

Abstract: Embodiments of the disclosure provide for systems and methods for searching video data for events and/or behaviors. An inference engine can be used to aide in the searching. In some embodiments, a user can specify various search criteria, for example, a video source(s), an event(s) or behavior(s) to search, and an action(s) to perform in the event of a successful search. The search can be performed by analyzing an object(s) found within scenes of the video data. An object can be identified by a number of attributes specified by the user. Once the search criteria has been received from the user, the video data can be received (or extracted from storage), the data analyzed for the specified events (or behaviors), and the specified action performed in the event a successful search occurs.

Abstract: An image display method includes: receiving, from a single camera, first and second image information for first and second captured images captured from different perspectives, the first image information having a first data density; selecting a portion of the first captured image for display with a higher level of detail than other portions of the first captured image, the selected portion corresponding to a first area of the first captured image; displaying the selected portion in a first displayed image, using a second data density relative to the selected portion of the first captured image; and displaying another portion of the first captured image, in a second displayed image, using a third data density; where the another portion of the first captured image is other than the selected portion of the first captured image; and where the third data density is lower than the second data density.

Abstract: Techniques are described for tracking moving objects using a plurality of security cameras. Multiple cameras may capture frames that contain images of a moving object. These images may be processed by the cameras to create metadata associated with the images of the objects. Frames of each camera's video feed and metadata may be transmitted to a host computer system. The host computer system may use the metadata received from each camera to determine whether the moving objects imaged by the cameras represent the same moving object. Based upon properties of the images of the objects described in the metadata received from each camera, the host computer system may select a preferable video feed containing images of the moving object for display to a user.

Abstract: Techniques are discussed for correcting optical aberrations that exist in surveillance domes that have spherical and non-spherical parts. For example, the image quality of a surveillance camera is reduced when it focuses on an object through a non-spherical base of a surveillance dome. This image quality reduction could potentially compromise the security of the area monitored by the surveillance camera by failing to provide enough detail to identify individuals or other objects of interest. Utilizing a corrective optical element to provide curvature to a wavefront that travels through the non-spherical base, however, helps preserve the image quality of the camera and thereby helps maintain the integrity of the surveillance system.

Abstract: Embodiments of the disclosure provide for systems and methods for creating metadata associated with a video data. The metadata can include data about objects viewed within a video scene and/or events that occur within the video scene. Some embodiments allow users to search for specific objects and/or events by searching the recorded metadata. In some embodiments, metadata is created by receiving a video frame and developing a background model for the video frame. Foreground object(s) can then be identified in the video frame using the background model. Once these objects are identified they can be classified and/or an event associated with the foreground object may be detected. The event and the classification of the foreground object can then be recorded as metadata.

Abstract: Systems, methods, and devices are disclosed for determining a zooming factor for a camera in a pan, tilt, and zoom (PTZ) camera tracking system to enable a camera to keep an object at a constant size within the camera's viewing area, despite changes in the object's distance from the camera. This provides a complement to a camera's pan and tilt tracking of the moving object. For example, a PTZ camera tracking system that determines an object to track, utilizes information regarding images of the object of interest are used to determine a zooming factor (or other zooming value) for a camera in the PTZ camera tracking system. This information includes variables such as tilt angles of one or more cameras and a reference zooming factor.