Abstract: A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.

Abstract: A computing system for identifying, describing, and sharing salient events depicted in images and videos executes feature detection algorithms on multimedia input (e.g., video and/or images). The computing system applies semantic reasoning techniques to the output of the feature detection algorithms. The computing system identifies salient event segments of the multimedia input as a result of the semantic reasoning. The computing system can incorporate the salient event segments into a visual presentation, such as a video clip. Alternatively or in addition, the computing system can generate a natural language description of the content of the multimedia input.

Abstract: A unified framework detects and classifies people interactions in unconstrained user generated images. Previous approaches directly map people/face locations in two-dimensional image space into features for classification. Among other things, the disclosed framework estimates a camera viewpoint and people positions in 3D space and then extracts spatial configuration features from explicit three-dimensional people positions.

Abstract: An entity interaction recognition system algorithmically recognizes a variety of different types of entity interactions that may be captured in two-dimensional images. In some embodiments, the system estimates the three-dimensional spatial configuration or arrangement of entities depicted in the image. In some embodiments, the system applies a proxemics-based analysis to determine an interaction type. In some embodiments, the system infers, from a characteristic of an entity detected in an image, an area or entity of interest in the image.

Abstract: A complex video event classification, search and retrieval system can generate a semantic representation of a video or of segments within the video, based on one or more complex events that are depicted in the video, without the need for manual tagging. The system can use the semantic representations to, among other things, provide enhanced video search and retrieval capabilities.

Abstract: A method for segmenting video data into foreground and background portions utilizes statistical modeling of the pixels. A statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system. The method for segmenting video data may be implemented in hardware.

Abstract: A method for structuring a debt that comprises: establishing a holding company as an owner of a closed block business entity, wherein the holding company is a subsidiary of a parent company and further wherein an on-going business is a subsidiary of the parent company; issuing debt from the holding company, wherein: (a) the debt is issued for raising capital for the parent company and the capital is provided to the on-going business; and (b) the debt is serviceable from the cash flow of the closed block business entity and the debt has a limited recourse only from the closed block business entity.

Abstract: A method for segmenting video data into foreground and background (324) portions utilizes statistical modeling of the pixels ? statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared (326) with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system The method for segmenting video data may be implemented in hardware.

Abstract: A video sequence of a field of view within an environment is received. Targets are detected in the video sequence. Target geo-positional information is received. Correspondences between the targets detected in the video sequence and the target geo-positional information are determined and used to calibrate the camera and to geo-register a field of view of the camera.

Abstract: A computer-based method for automatic detection of water regions in a video include the steps of estimating a water map of the video and outputting the water map to an output medium, such as a video analysis system. The method may further include the steps of training a water model from the water map; re-classifying the water map using the water model by detecting water pixels in the video; and refining the water map.

Abstract: A method for segmenting video data into foreground and background (324) portions utilizes statistical modeling of the pixels ? statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared (326) with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system The method for segmenting video data may be implemented in hardware.

Abstract: A computer-readable medium contains software that, when read by a computer, causes the computer to perform a method for wide-area site-based surveillance.

Abstract: A computer-based method for automatic detection of water regions in a video include the steps of estimating a water map of the video and outputting the water map to an output medium, such as a video analysis system. The method may further include the steps of training a water model from the water map; re-classifying the water map using the water model by detecting water pixels in the video; and refining the water map.

Abstract: A computer-readable medium contains software that, when read by a computer, causes the computer to perform a method for wide-area site-based surveillance.

Abstract: Tracking and surveillance methods and systems for monitoring objects passing in front of non-overlapping cameras. Invention finds corresponding tracks from different cameras and works out which object passing in front of the camera(s) made the tracks, in order to track the object from camera to camera. The invention uses an algorithm to learn inter-camera spatial temporal probability using Parzen windows, learns inter-camera appearance probabilities using distribution of Bhattacharyya distances between appearance models, establishes correspondences based on Maximum A Posteriori (MAP) framework combining both spatial temporal and appearance probabilities, and updates learned probabilities throughout the lifetime of the system.

Abstract: A video sequence of a field of view within an environment is received. Targets are detected in the video sequence. Target geo-positional information is received. Correspondences between the targets detected in the video sequence and the target geo-positional information are determined and used to calibrate the camera and to geo-register a field of view of the camera.

Abstract: A method for segmenting video data into foreground and background portions utilizes statistical modeling of the pixels. A statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system. The method for segmenting video data may be implemented in hardware.

Abstract: A method for structuring a debt that comprises: establishing a holding company as an owner of a closed block business entity, wherein the holding company is a subsidiary of a parent company and further wherein an on-going business is a subsidiary of the parent company; issuing debt from the holding company, wherein: (a) the debt is issued for raising capital for the parent company and the capital is provided to the on-going business; and (b) the debt is serviceable from the cash flow of the closed block business entity and the debt has a limited recourse only from the closed block business entity.

Abstract: A video camera may overlook a monitored area from any feasible position. An object flow estimation module monitor the moving direction of the objects in the monitored area. It may separate the consistently moving objects from the other objects. A object count estimation module may compute the object density (e.g. crowd). A object density classification module may classify the density into customizable categories.

Abstract: A method for structuring an equity issue comprising: (a) establishing a holding company as an owner of a closed block business entity, wherein the holding company is a subsidiary of a parent company and further wherein an on-going business is a subsidiary of the parent company; (b) representing an on-going business by a first class of common stock issued from the parent company; (c) issuing a second class of common stock in the parent company, wherein the second class of common stock represents an ownership interest in the closed block business entity and wherein the closed block business entity is a lower growth and lower margin business than the on-going business; and (d) classifying proceeds received from the issuance of the second class of common stock as assets of the on-going business.