Abstract: The present invention provides a system and method for processing real-time rapid capture, annotation and creation of an annotated hyper-video map for environments. The method includes processing video, audio and GPS data to create the hyper-video map which is further enhanced with textual, audio and hyperlink annotations that will enable the user to see, hear, and operate in an environment with cognitive awareness. Thus, this annotated hyper-video map provides a seamlessly navigable, situational awareness and indexable high-fidelity immersive visualization of the environment.

Abstract: A method and apparatus for performing video surveillance of a field of view is disclosed. In one embodiment, a method for performing surveillance of the field of view includes monitoring the field of view and detecting a moving object in the field of view, where the motion is detected based on a spatio-temporal signature (e.g., a set of descriptive feature vectors) of the moving object.

Abstract: A sentient system combines detection, tracking, and immersive visualization of a cluttered and crowded environment, such as an office building, terminal, or other enclosed site using a network of stereo cameras. A guard monitors the site using a live 3D model, which is updated from different directions using the multiple video streams. As a person moves within the view of a camera, the system detects its motion and tracks the person's path, it hands off the track to the next camera when the person goes out of that camera's view. Multiple people can be tracked simultaneously both within and across cameras, with each track shown on a map display. The track system includes a track map browser that displays the tracks of all moving objects as well as a history of recent tracks and a video flashlight viewer that displays live immersive video of any person that is being tracked.

Abstract: A system and method for identifying objects, particularly vehicles, between two non-overlapping cameras. More specifically, the method and system determines whether a vehicle depicted in an image captured by a first camera is the same vehicle or a different vehicle than a vehicle depicted in an image captured by a second camera. This intra-camera analysis determines whether the vehicle viewed by the first camera is the same as the vehicle viewed by the second camera, without directly matching the two vehicle images, thus eliminating the problems and inaccuracies caused by disparate environmental conditions acting on the two cameras, such as dramatic appearance and aspect changes.

Abstract: A method and apparatus for tracking a movable object using a plurality of images, each of which is separated by an interval of time is disclosed. The plurality of images includes first and second images. The method and apparatus include elements for aligning the first and second images as a function of (i) at least one feature of a first movable object captured in the first image, and (ii) at least one feature of a second movable object captured in the second image; and after aligning the first and second images, comparing at least one portion of the first image with at least one portion of the second image.

Abstract: A method and apparatus for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras is disclosed The method includes collecting at least one two pairs of feature maps, where the at least one two pairs of feature maps are derived from features of objects captured in the images. The method further includes computing, as a function of at least one two pairs of feature maps, at least one first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class.

Abstract: A method and apparatus for automatically generating a three-dimensional computer model from a “point cloud” of a scene produced by a laser radar (LIDAR) system. Given a point cloud of an indoor or outdoor scene, the method extracts certain structures from the imaged scene, i.e., ceiling, floor, furniture, rooftops, ground, and the like, and models these structures with planes and/or prismatic structures to achieve a three-dimensional computer model of the scene. The method may then add photographic and/or synthetic texturing to the model to achieve a realistic model.

Abstract: A method and apparatus for video surveillance is disclosed. In one embodiment, a sequence of scene imagery representing a field of view is received. One or more moving objects are identified within the sequence of scene imagery and then classified in accordance with one or more extracted spatio-temporal features. This classification may then be applied to determine whether the moving object and/or its behavior fits one or more known events or behaviors that are causes for alarm.

Abstract: A unified approach, a fusion technique, a space-time constraint, a methodology, and system architecture are provided. The unified approach is to fuse the outputs of monocular and stereo video trackers, RFID and localization systems and biometric identification systems. The fusion technique is provided that is based on the transformation of the sensory information from heterogeneous sources into a common coordinate system with rigorous uncertainties analysis to account for various sensor noises and ambiguities. The space-time constraint is used to fuse different sensor using the location and velocity information. Advantages include the ability to continuously track multiple humans with their identities in a large area. The methodology is general so that other sensors can be incorporated into the system. The system architecture is provided for the underlying real-time processing of the sensors.

Abstract: A method and apparatus for recognizing an object, comprising providing a set of scene features from a scene, pruning a set of model features, generating a set of hypotheses associated with the pruned set of model features for the set of scene features, pruning the set of hypotheses, and verifying the set of pruned hypotheses is provided.

Abstract: A method and apparatus for processing a video sequence is disclosed. The apparatus may include a video processor for detecting and tracking at least one identifiable face in a video sequence. The method may include performing face detection of at least one identifiable face, selecting a face template including face features used to represent the at least one identifiable face, processing the video sequence to detect faces similar to the at least one identifiable face, and tracking the at least one identifiable face in the video sequence.

Abstract: A scalable architecture for providing real-time multi-camera distributed video processing and visualization. An exemplary system comprises at least one video capture and storage system for capturing and storing a plurality of input videos, at least one vision based alarm system for detecting and reporting alarm situations or events, and at least one video rendering system (e.g., a video flashlight system) for displaying an alarm situation in a context that speeds up comprehension and response. One advantage of the present architecture is that these systems are all scalable, such that additional sensors (e.g., cameras, motion sensors, infrared sensors, chemical sensors, biological sensors, temperature sensors and like) can be added in large numbers without overwhelming the ability of security forces to comprehend the alarm situation.

Abstract: Method and apparatus for dynamically placing sensors in a 3D model is provided. Specifically, in one embodiment, the method selects a 3D model and a sensor for placement into the 3D model. The method renders the sensor and the 3D model in accordance with sensor parameters associated with the sensor and parameters desired by a user. In addition, the method determines whether an occlusion to the sensor is present.

Abstract: A method and apparatus for accurately computing parallax information as captured by imagery of a scene. The method computes the parallax information of each point in an image by computing the parallax within windows that are offset with respect to the point for which the parallax is being computed. Additionally, parallax computations are performed over multiple frames of imagery to ensure accuracy of the parallax computation and to facilitate correction of occluded imagery.

Abstract: A system and method that detects independently moving objects in 3D scenes which are viewed under camera motion progressively applies constraints to the images to ensure the stability of the constraints. The system first calculates 2D view geometry constraints for a set of images. These constraints are tested to determine if the imaged scene exhibits significant 3D characteristics. If it does, then 3D shape constraints, are applied to the set of images. The 3D shape constraints are themselves constrained by the 2D view geometry constraints. The set of images is then tested to identify areas that are inconsistent with the 2D or 3D constraints. These areas correspond to the moving objects. The 2D view geometry constraints are calculated by computing a dominant image alignment for successive pairs of images and then computing constrained epipolar transformations for the two image pairs. This 2D view geometry is further refined based on a plurality of target point correspondences among the plurality of frames.

Abstract: A method of constructing an image mosaic comprising the steps of selecting source images, aligning the source images, selecting source segments, enhancing the images, and merging the images to form the image mosaic is disclosed. An apparatus for constructing an image mosaic comprising means for selecting source images, means for aligning the source images, means for selecting source image segments, means for enhancing the images, and means for merging the images to form the image mosaic is also disclosed. The process may be performed automatically by the system or may be guided interactively by a human operator. Applications include the construction of photographic quality prints form video and digital camera images.