Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: In an example embodiment, an image based vehicle detection and measuring apparatus that employs an accelerated, structured, search method is described for quickly finding the extrema of a multivariable function. The input domain of the function is determined. The method exploits information as it becomes available, calculating a best possible value with the information available so far, and terminating further evaluation when the best possible value does not exceed the extreme value found so far. Ordering and best guess schemes are added to the best possible value idea to accelerate it further. The method is applied to speed up an image processing problem, an example of which is given, but has general application, for example, in fields such as vehicle detection.

Abstract: A system and method for autonomous tracking of aerial targets in real space in a featureless background includes capturing and processing first and second images. A resultant image is produced which includes blobs corresponding to elements in the real space. The resultant image is further processed, together with either or both of the first and second images. One of the blobs is analyzed, classified, and tracked as a target.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: A system for autonomous tracking of aerial targets in real space. The imaging means captures and aligns first and second images. A normalized correlation operation initiates a process for producing a resultant image including blobs corresponding to elements in the real space, despite the presence of a homogenous aerial background. One of the blobs is analyzed, classified, and tracked as a target.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: A surveillance system and method includes imaging means for processing images so that objects in the foreground are detected in the background and threats are identified. In the method, the imaging means acquires images and an initial background model is constructed from those images. Pixels are classified as either background or foreground for subsequent processing stages. In some embodiments, the imaging means is fixed in location and attitude, while in other embodiments, the imaging means is mounted to a moving platform and can alter its attitude. In such mobile applications, the system exploits geo-referencing as an aid in determining information about the pixels.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: A multi-object zonal traffic detection framework analyzes temporal and spatial information from one or more sensors in a classification engine that identifies and differentiates objects within a single identified traffic detection zone. The classification engine applies a whole scene analysis and an adaptive background zone detection model to classify cars, trucks, bicycles, pedestrians, incidents, and other objects within the single identified traffic detection zone and generates counts for each object type for traffic system management.

Abstract: An autonomous lock-on target tracking system and method with imaging means for a real space. The imaging means captures and aligns first and second images. A frame-differencing operation produces a resultant image including blobs corresponding to elements in the real space. One of the blobs is analyzed, classified, and tracked as a target.

Abstract: A video camera surveillance system includes a camera for acquiring a video stream and converting terrain space into image space and a method for processing the video stream so that objects in the foreground are detected in the background and threats are identified. In the method, the camera acquires the video stream, images in the video stream are stabilized, an initial background model is constructed, and pixels are classified as either background or foreground for subsequent processing stages such as morphological filtering, image segmentation, and background model updating. In some embodiments of the invention, the camera is fixed in location and attitude, while in other embodiments, the camera is mounted to a moving platform and can alter its attitude.

Abstract: An autonomous lock-on target tracking system and method with geospatial-aware PTZ cameras includes a camera imaging a terrain space. The camera acquires images, and first and second images are aligned. A frame-differencing operation produces a resultant image including blobs corresponding to elements in the terrain space. One of the blobs is classified as an object and tracked as a target. The target is tracked by determining the distance between a centroid of the target and a center of a field of view of the camera, and instructing the camera to move through the distance. The distance is continually updated as the camera and the target move. Disclosed are also methods for deploying the georeferencing enabled version of such PTZ camera on stationary and mobile land, sea and air platforms.

Abstract: A traffic management apparatus and system performs data processing functions on images in a video data stream to analyze differences between portions of the images and account for movement of a camera at a traffic intersection or other such environment. The traffic management apparatus and system is configured to be placed on a span wire or other non-fixed position at or near the traffic intersection.

Abstract: An autonomous lock-on target tracking system and method with geospatial-aware PTZ cameras includes a camera imaging a terrain space. The camera acquires images, and first and second images are aligned. A frame-differencing operation produces a resultant image including blobs corresponding to elements in the terrain space. One of the blobs is classified as an object and tracked as a target. The target is tracked by determining the distance between a centroid of the target and a center of a field of view of the camera, and instructing the camera to move through the distance. The distance is continually updated as the camera and the target move.

Abstract: A traffic management apparatus and system performs data processing functions on images in a video data stream to analyze differences between portions of the images and account for movement of a camera at a traffic intersection or other such environment. The traffic management apparatus and system is configured to be placed on a span wire or other non-fixed position at or near the traffic intersection.

Abstract: In an example embodiment, an image based vehicle detection and measuring apparatus that employs an accelerated, structured, search method is described for quickly finding the extrema of a multivariable function. The input domain of the function is determined. The method exploits information as it becomes available, calculating a best possible value with the information available so far, and terminating further evaluation when the best possible value does not exceed the extreme value found so far. Ordering and best guess schemes are added to the best possible value idea to accelerate it further. The method is applied to speed up an image processing problem, an example of which is given, but has general application, for example, in fields such as vehicle detection.