Abstract: A method to dynamically stabilize a target image formed on an image plane of an imaging device located in a moving vehicle. The method includes setting an origin in the image plane of the imaging device at an intersection of a first axis, a second axis and a third axis, imaging a target so that an image centroid of the target image is at the origin of the image plane, monitoring sensor data indicative of a motion of the vehicle, and generating pan and tilt output to stabilize the image centroid at the origin in the image plane to compensate for vehicle motion and target motion. The pan and tilt output are generated by implementing exponentially stabilizing control laws. The implementation of the exponentially stabilizing control laws is based at least in part on the sensor data.

Abstract: A system to identify targets comprising a camera module to track a target and to generate a relatively stable image of the target while the target moves with respect to the camera module, sensors to sense a movement of the camera module and to generate sensor data, a memory storing a database of possible targets and a programmable processor communicatively coupled to each of the memory, the camera module and the sensors. The programmable processor receives signals comprising information indicative of the image from the camera module and executes instructions in an instruction module. The instructions comprise exponentially stabilizing control laws based at least in part on the sensor data. The programmable processor executes instructions in the instruction module to determine a pattern match between the stable image of the target and one of the possible targets in the database.

Abstract: A method to dynamically stabilize a target image formed on an image plane of an imaging device located in a moving vehicle. The method includes setting an origin in the image plane of the imaging device at an intersection of a first axis, a second axis and a third axis, imaging a target so that an image centroid of the target image is at the origin of the image plane, monitoring sensor data indicative of a motion of the vehicle, and generating pan and tilt output to stabilize the image centroid at the origin in the image plane to compensate for vehicle motion and target motion. The pan and tilt output are generated by implementing exponentially stabilizing control laws. The implementation of the exponentially stabilizing control laws is based at least in part on the sensor data.

Abstract: A system for autonomous object tracking with static camera arrangements. Each camera arrangement may minimally have a pan-tilt-zoom camera and a range or depth sensor. Imaging may provide coordinates and depth information of a tracked object. Measurements of an image centroid position and width may be obtained with processing. Maintaining an image at the center of a camera screen may be attained at a pixel width of the image. Estimation and prediction of object size and position may be processed for providing pan, tilt and zoom rates for the camera. Pan, tilt and zoom latency may be accounted for in the system. There may be a number of camera arrangements where tracking of the object may be handed off by one camera arrangement to another.

Abstract: Facial detection and tracking systems and methods within a wide field of view are disclosed. A facial detection and tracking system in accordance with an illustrative embodiment of the present invention can include a wide field of view camera for detecting and tracking one or more objects within a wider field of view, and at least one narrower field of view camera for obtaining a higher-resolution image of each object located within a subset space of the wider field of view. The wide field of view camera can be operatively coupled to a computer or other such device that determines the subset space location of the individual within the wider field of view, and then tasks one or more of the narrower field of view cameras covering the subset space location to obtain a high-resolution image of the object.

Abstract: A system for tracking objects across an area having a network of cameras with overlapping and non-overlapping fields of view. The system may use a combination of color, shape, texture and/or multi-resolution histograms for object representation or target modeling for the tacking of an object from one camera to another. The system may include user and output interfacing.

Abstract: A cooperative camera network involving segmenting an image of an object and extracting a color signature from it. The color signature may be matched with the other signatures in an attempt to identify the object. There also can be combining and fusing the tracking of people and objects with image processing and the identification of the people and objects being tracked in an area or facility.

Abstract: Thermal infrared image data of at least a region of a face of a person in an enclosure is provided. The enclosure, for example, may include a first enclosed volume and a second enclosed volume physically separated from the first enclosed volume. The first enclosed volume may include an entrance door sized to allow a person to enter the first enclosed volume. The enclosure provides a controlled environment for performing measurements (e.g., capturing thermal infrared image data) for use in determining a physiological state of a person (e.g., anxiety, deception, etc.).

Abstract: Thermal infrared image data of at least a region of a face of a person in an enclosure is provided. The enclosure, for example, may include a first enclosed volume and a second enclosed volume physically separated from the first enclosed volume. The first enclosed volume may include an entrance door sized to allow a person to enter the first enclosed volume. The enclosure provides a controlled environment for performing measurements (e.g., capturing thermal infrared image data) for use in determining a physiological state of a person (e.g., anxiety, deception, etc.).

Abstract: A face detection and recognition system having several arrays imaging a scene in the infrared and visible spectrums. The system may use weighted subtracting and thresholding to distinguish human skin in a sensed image. A feature selector may locate a face in the image. The image may be cropped with a frame or border incorporating essentially only the face. The border may be superimposed on images from an infrared imaging array and the visible imaging array. Sub-images containing the face may be extracted from within the border on the infrared and visible images, respectively, and compared with a database of face information to attain recognition of the face. Confidence levels of recognition for infrared and visible imaged faces may be established. A resultant confidence level of recognition may be determined from these confidence levels. Infrared lighting may be used as needed to illuminate the scene.

Abstract: A face detection and recognition system having several arrays imaging a scene at different bands of the infrared spectrum. The system may use weighted subtracting and thresholding to distinguish human skin in a sensed image. A feature selector may locate a face in the image. The face may be framed or the image cropped with a frame or border to incorporate essentially only the face. The border may be superimposed on an image direct from an imaging array. A sub-image containing the face may be extracted from within the border and compared with a database of face information to attain recognition of the face. A level of recognition of the face may be established. Infrared lighting may be used as needed to illuminate the scene.

Abstract: A system for providing stand-off biometric verification of a driver of a vehicle while the vehicle is moving and/or a person on foot at a control gate, including an RFID vehicle tag reader, an RFID personal smart card reader and a facial detection and recognition (verification) system. The driver carries a RFID personal smart card that stores personal information of the driver and a face template of the driver. The vehicle carries a RFID vehicle tag that stores information regarding the vehicle. When the vehicle approaches the control gate, the RFID vehicle tag reader reads data from the RFID vehicle tag and the RFID personal tag reader reads data from the RFID personal smart card. The facial detection and verification system scans and reads a facial image for the driver. All the data and facial images detected by the readers are sent to a local computer at the control gate for further processing (final face verification).

Abstract: Methods and systems for the unsupervised learning of events contained within a video sequence, including apparatus and interfaces for implementing such systems and methods, are disclosed. An illustrative method in accordance with an exemplary embodiment of the present invention may include the steps of providing a behavioral analysis engine, initiating a training phase mode within the behavioral analysis engine and obtaining a feature vector including one or more parameters relating to an object located within an image sequence, and then analyzing the feature vector to determine a number of possible event candidates. The behavioral analysis engine can be configured to prompt the user to confirm whether an event candidate is a new event, an existing event, or an outlier. Once trained, a testing/operational phase mode of the behavioral analysis engine can be further implemented to detect the occurrence of one or more learned events, if desired.

Abstract: Monitoring systems, devices, and methods for monitoring one or more objects within an environment are disclosed. An illustrative monitoring device in accordance with the present invention can include an image detector, an on-board image processor, and communication means for transmitting an imageless signal to a remote location. The image processor can be configured to run one or more routines that can be used to determine a number of parameters relating to each object detected. In some embodiments, the monitoring device can be configured to run an image differencing routine that can be used to initially detect the presence of motion. Once motion is detected, the monitoring device can be configured to initiate a higher rate mode wherein image frames are processed at a higher frame rate to permit the image processor to compute higher-level information about the moving object.

Abstract: Imaging methods and systems for concealed weapon detection are disclosed. In an active mode, a target can be illuminated by a wide-band RF source. A mechanically scanned antenna, together with a highly sensitive wide-band receiver can then collect and process the signals reflected from the target. In a passive mode, the wide-band receiver detects back-body radiation emanating from the target and possesses sufficient resolution to separate different objects. The received signals can then be processed via a computer and displayed on a display unit thereof for further analysis by security personnel.

Abstract: Imaging methods and systems for concealed weapon detection are disclosed. In an active mode, a target can be illuminated by a wide-band RF source. A mechanically scanned antenna, together with a highly sensitive wide-band receiver can then collect and process the signals reflected from the target. In a passive mode, the wide-band receiver detects back-body radiation emanating from the target and possesses sufficient resolution to separate different objects. The received signals can then be processed via a computer and displayed on a display unit thereof for further analysis by security personnel.

Abstract: A method and system for use in monitoring a search area includes the provision of a plurality of time varying distributions for each pixel of image data representative of a search area. The plurality of time varying distributions for each pixel are ordered based on a probability of the time varying distribution being representative of background or foreground information in the search area. For each pixel, an attempt to match update pixel value data to each of all of the plurality of time varying distributions provided for the corresponding pixel is performed to determine if the update pixel value data is representative of background or foreground information in the search area.