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:
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 system for tracking at least one object, comprising: a plurality of communicatively connected visual sensing units configured to capture visual data related to the at least one object; and a manager component communicatively connected to the plurality of visual sensing units, where the manager component is configured to assign one visual sensing unit to act as a visual sensing unit in a master mode and at least one visual sensing unit to act as a visual sensing unit in a slave mode, transmit at least one control signal to the plurality of visual sensing units, and receive the visual data from the plurality of visual sensing units.
Abstract:
A scalable method and apparatus is described to provide personalized interactive visualization of a plurality of compressed image data to a plurality of concurrent users. A plurality of image sources are digitally processed in the compressed domain to provide controllable enhanced user-specific interactive visualization with support for adjustment in viewing parameters such frame-rate, field of view, resolution, color format, viewpoint and bandwidth.
Abstract:
A system for tracking at least one object is disclosed. The system includes a plurality of communicatively connected visual sensing units configured to capture visual data related to the at least one object The system also includes a manager component communicatively connected to the plurality of visual sensing units. The manager component is configured to assign one visual sensing unit to act as a visual sensing unit in a master mode and at least one visual sensing unit to act as a visual sensing unit in a slave mode. The manager component is further configured to transmit at least one control signal to the plurality of visual sensing units, and receive the visual data from the plurality of visual sensing units.
Abstract:
A scalable method and apparatus is described to provide personalized interactive visualization of a plurality of compressed image data to a plurality of concurrent users. A plurality of image sources are digitally processed in the compressed domain to provide controllable enhanced user-specific interactive visualization with support for adjustment in viewing parameters such frame-rate, field of view, resolution, color format, viewpoint and bandwidth.
Abstract:
Method for tracking an object recorded within a selected frame of a sequence of frames of video data, using a plurality of layers, where at least one object layer of the plurality of layers represents the object includes initializing layer ownership probabilities for pixels of the selected frame using a non-parametric motion model, estimating a set of motion parameters of the plurality of layers for the selected frame using a parametric maximization algorithm and tracking the object. The non-parametric motion model is optical flow and includes warping the mixing probabilities, the appearances of the plurality of layers, and the observed pixel data from the pixels of the preceding frame to the pixels of the selected frame to initialize the layer ownership probabilities for the pixels of the selected frame.
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 method and apparatus for detecting objects (e.g., bags, vehicles, etc.) left in a field of view are disclosed. A long-term representation and a short-term representation of the field of view are constructed, and a difference between the long-term representation and the short-term representation is calculated. One or more criteria may optionally be applied to this difference to determine whether the difference represents an object that was left in the field of view.
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.