Patent application number | Description | Published |
20090027334 | METHOD FOR CONTROLLING A GRAPHICAL USER INTERFACE FOR TOUCHSCREEN-ENABLED COMPUTER SYSTEMS - A method for controlling a graphical user interface (GUI) for a touchscreen-enabled computer systems provides a variety of software methods (tools) provide for high-fidelity control of the user interface. The TrackScreen tool provides finger-friendly mouse functions such as scrolling, dragging and clicking. The Magnifier application continuously captures the current screen image, and displays a magnified subset of it. Selecting within this magnified area with a pointing device (mouse, touchscreen, digitizer, etc) causes the application to simulate the action on the portion of the screen corresponding to the point in the magnified image that was selected. A KeyBoard application, a keyboard is rendered on screen, with sufficient size that the individual keys are easily selectable with an unaided finger. The Common Tasks Tool or CTT) allows common keyboard shortcuts, mouse events, and other user interface events to be specified in a configuration file and represented on screen as a large, easy-to-click button. The Touchscreen Task Switcher is invoked using any interface (software or hardware) element, and visually takes up the entire screen. The Touchscreen Snapshot utility ties in with an external camera with a physical button on it. The Window Template Manager (WTM), is used to specify, and then instantiate, the position and sizes of multiple windows for use with a touchscreen display. The Touch Portal is a full-screen application with a set of customizable buttons representing applications and other tools. | 01-29-2009 |
20090074248 | GESTURE-CONTROLLED INTERFACES FOR SELF-SERVICE MACHINES AND OTHER APPLICATIONS - A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines. | 03-19-2009 |
20090116692 | REALTIME OBJECT TRACKING SYSTEM - A real-time computer vision system tracks one or more objects moving in a scene using a target location technique which does not involve searching. The imaging hardware includes a color camera, frame grabber and processor. The software consists of the low-level image grabbing software and a tracking algorithm. The system tracks objects based on the color, motion and/or shape of the object in the image. A color matching function is used to compute three measures of the target's probable location based on the target color, shape and motion. The method then computes the most probable location of the target using a weighting technique. Once the system is running, a graphical user interface displays the live image from the color camera on the computer screen. The operator can then use the mouse to select a target for tracking. The system will then keep track of the moving target in the scene in real-time. | 05-07-2009 |
20090274339 | Behavior recognition system - A system for recognizing various human and creature motion gaits and behaviors is presented. These behaviors are defined as combinations of “gestures” identified on various parts of a body in motion. For example, the leg gestures generated when a person runs are different than when a person walks. The system described here can identify such differences and categorize these behaviors. Gestures, as previously defined, are motions generated by humans, animals, or machines. Multiple gestures on a body (or bodies) are recognized simultaneously and used in determining behaviors. If multiple bodies are tracked by the system, then overall formations and behaviors (such as military goals) can be determined. | 11-05-2009 |
20110102419 | ORIENTATION INVARIANT OBJECT IDENTIFICATION USING MODEL-BASED IMAGE PROCESSING - A system for performing object identification combines pose determination, EO/IR sensor data, and novel computer graphics rendering techniques. A first module extracts the orientation and distance of a target in a truth chip given that the target type is known. A second is a module identifies the vehicle within a truth chip given the known distance and elevation angle from camera to target. Image matching is based on synthetic image and truth chip image comparison, where the synthetic image is rotated and moved through a 3-Dimensional space. To limit the search space, it is assumed that the object is positioned on relatively flat ground and that the camera roll angle stays near zero. This leaves three dimensions of motion (distance, heading, and pitch angle) to define the space in which the synthetic target is moved. A graphical user interface (GUI) front end allows the user to manually adjust the orientation of the target within the synthetic images. The system also includes the generation of shadows and allows the user to manipulate the sun angle to approximate the lighting conditions of the test range in the provided video. | 05-05-2011 |
20120263348 | ORIENTATION INVARIANT OBJECT IDENTIFICATION USING MODEL-BASED IMAGE PROCESSING - A system for performing object identification combines pose determination, EO/IR sensor data, and novel computer graphics rendering techniques. A first module extracts the orientation and distance of a target in a truth chip given that the target type is known. A second module identifies the vehicle within a truth chip given the known distance and elevation angle from camera to target. Image matching is based on synthetic image and truth chip image comparison, where the synthetic image is rotated and moved through a 3-Dimensional space. It is assumed that the object is positioned on relatively flat ground and that the camera roll angle stays near zero. This leaves three dimensions of motion (distance, heading, and pitch angle) to define the space in which the synthetic target is moved. A graphical user interface (GUI) front end allows the user to manually adjust the orientation of the target within the synthetic images. | 10-18-2012 |
20140071037 | BEHAVIOR RECOGNITION SYSTEM - A system for recognizing various human and creature motion gaits and behaviors is presented. These behaviors are defined as combinations of “gestures” identified on various parts of a body in motion. For example, the leg gestures generated when a person runs are different than when a person walks. The system described here can identify such differences and categorize these behaviors. Gestures, as previously defined, are motions generated by humans, animals, or machines. Multiple gestures on a body (or bodies) are recognized simultaneously and used in determining behaviors. If multiple bodies are tracked by the system, then overall formations and behaviors (such as military goals) can be determined. | 03-13-2014 |
20140320486 | ORIENTATIOIN INVARIANT OBJECT IDENTIFICATION USING MODEL-BASED IMAGE PROCESSING - A system for performing object identification combines pose determination, EO/IR sensor data, and novel computer graphics rendering techniques. A first module extracts the orientation and distance of a target in a truth chip given that the target type is known. A second is a module identifies the vehicle within a truth chip given the known distance and elevation angle from camera to target. Image matching is based on synthetic image and truth chip image comparison, where the synthetic image is rotated and moved through a 3-Dimensional space. To limit the search space, it is assumed that the object is positioned on relatively flat ground and that the camera roll angle stays near zero. This leaves three dimensions of motion (distance, heading, and pitch angle) to define the space in which the synthetic target is moved. A graphical user interface (GUI) front end allows the user to manually adjust the orientation of the target within the synthetic images. The system also includes the generation of shadows and allows the user to manipulate the sun angle to approximate the lighting conditions of the test range in the provided video. | 10-30-2014 |