Abstract: Video segmentation wherein scene images of subjects and background are captured by video and are automatically segmented according to subject content, as by system determination of the nature of subjects, but segmentation of the subjects can be compromised by visual noise. Segmentation transformations of an original background and foreground images in the scenes are provided as a terrain map, and the segmentation may also incorporate noise blobs. Automatic segmentation threshold adaptation is based on measuring the segmentation noise while holding the number count of noise blobs constant, whereby to achieve noise-adaptive segmentation gain. Automatic threshold adaptation within multiple areas of the scene results in different possible thresholds in different areas based on the amount of segmentation noise in each area. Segmentation is improved accordingly.

Abstract: Method and system for image data analysis, by making use of a Terrain Map Summary Element (TMSE) data structure, in which a Terrain Map data structure provides processed primitive data about each 2×2 kernel of pixels from an original image. The new TMSE is a hierarchical multiple-level or tiered structure of such Terrain Map elements, in which each successive Terrain Map level summarizes, for example, 16 lower level elements or member. By providing such a hierarchical nature of the map elements, richness is enhanced by each higher element because every element of each successively higher level map summarizes the data from elements of the lower level map. For example, in a five-level Terrain Map Summary Element structure according to the disclosure, each element or member of the fifth level contains information summarizing data about 256K pixels.

Abstract: Methodology of implementing complex behavior recognition in an intelligent video system includes multiple event detection defining activity in different areas of the scene (“What”), multiple masks defining areas of a scene (“Where”), configurable time parameters (“When”), and a configurable logic inference engine to allow Boolean logic analysis based on any combination of logic-defined events and masks. Events are detected in a video scene that consists of one or more camera views termed a “virtual view”. The logic-defined event is a behavioral event connoting behavior, activities, characteristics, attributes, locations and/or patterns of a target subject of interest. A user interface allows a system user to select behavioral events for logic definition by the Boolean equation in accordance with a perceived advantage, need or purpose arising from context of system use.

Abstract: Video image ghost detection in a security/surveillance CCTV system for automated image analysis. At least one pass of a video frame produces a terrain map with video content-indicating parameters, by which are analyzed behavior of objects, e.g., people and vehicles, moving in a scene having a background and a foreground, while detecting “ghost” images of objects that were in an adaptive background of the scene but are moving, by measuring a horizontal smoothness and/or vertical smoothness by segmentation procedure by which an object outline is predicted. The examination of segmented background and foreground image portions is conducted by software process to determine existence of such outline as by edge detection or changes in texture. Probability of an image ghost in either the background or foreground, or both, is calculated.

Abstract: Object selective video analysis and recordation system in which video camera output is recorded media with reduction of the amount of the recording media, with preservation of intelligence content of images of objects appearing against a background scene. Preset knowledge of symbolic categories of scene objects and analysis of object attributes is provided. Spatial resolution and temporal resolution of objects are automatically varied per preset criteria based on predetermined interest in object attributes while recording both background and object video. A system user can query recorded images by content to recall data according to specified symbolic content. So-called intelligent pruning allows changes in criteria for data storage or archiving to “prune” (cull or remove data) based upon such changes in criteria. Under software control, the system carries out pruning “after-the-fact,” i.e., after data has previously been identified by the system as significant enough for storage or archive.

Abstract: The present invention involves a system for automatically screening closed circuit television (CCTV) cameras for large and small scale security systems, as used for example in parking garages. The system includes six primary software elements, each of which performs a unique function within the operation of the security system to provide intelligent camera selection for operators, resulting in a marked decrease of operator fatigue in a CCTV system. Real-time image analysis of video data is performed wherein a single pass of a video frame produces a terrain map which contains parameters indicating the content of the video. Based on the parameters of the terrain map, the system is able to make decisions about which camera an operator should view based on the presence and activity of vehicles and pedestrians, furthermore, discriminating vehicle traffic from pedestrian traffic.

Abstract: The present invention involves a system for automatically screening closed circuit television (CCTV) cameras for large and small scale security systems, as used for example in parking garages. The system includes six primary software elements, each of which performs a unique function within the operation of the security system to provide intelligent camera selection for operators, resulting in a marked decrease of operator fatigue in a CCTV system. Real-time image analysis of video data is performed wherein a single pass of a video frame produces a terrain map which contains parameters indicating the content of the video. Based on the parameters of the terrain map, the system is able to make decisions about which camera an operator should view based on the presence and activity of vehicles and pedestrians, furthermore, discriminating vehicle traffic from pedestrian traffic.