Abstract: Systems and method of compensating for tracking motion of an object are disclosed. One such method includes receiving a series of images captured by each of a plurality of image capture devices. The image capture devices are arranged in an orthogonal configuration of two opposing pairs. The method further includes computing a series of positions of the object and orientations of the object, by processing the images captured by each of the plurality of image capture devices.

Abstract: Systems and method of compensating for tracking motion of an object are disclosed. One such method includes receiving a series of images captured by each of a plurality of image capture devices. The image capture devices are arranged in an orthogonal configuration of two opposing pairs. The method further includes computing a series of positions of the object and orientations of the object, by processing the images captured by each of the plurality of image capture devices.

Abstract: Apparatus, methods, systems and devices for identifying and tracking a human hand in a video. The steps for identifying the hand includes detecting parallel lines (bars), detecting curved fingertips (curves), grouping the detected parallel lines and curved fingertips according to a parallel line decision tree and a curved fingertip decision tree, respectively, and merging the parallel line group and the curved fingertip group to identify candidate hands.

Abstract: Visual methods and systems are described for detecting alertness and vigilance of persons under conditions of fatigue, lack of sleep, and exposure to mind altering substances such as alcohol and drugs. In particular, the intention can have particular applications for truck drivers, bus drivers, train operators, pilots and watercraft controllers and stationary heavy equipment operators, and students and employees during either daytime or nighttime conditions. The invention robustly tracks a person's head and facial features with a single on-board camera with a fully automatic system, that can initialize automatically, and can reinitialize when it need's to and provide outputs in realtime. The system can classify rotation in all viewing direction, detects' eye/mouth occlusion, detects' eye blinking, and recovers the 3D(three dimensional) gaze of the eyes. In addition, the system is able to track both through occlusion like eye blinking and also through occlusion like rotation.

Abstract: Disclosed is a two step process for automatically finding a human face in an electronically digitized image (for example, taken by handheld digital cameras and digital video-cameras such as cam-corders), and for confirming the existence of the face by examining facial features. Step 1 is to detect the human face and is accomplished in stages that include enhancing the digital image with a blurring filter and edge enhancer in order to better set forth the unique facial features such as wrinkles, and curved shapes of a facial image. After prefiltering, preselected curves sometimes referred to as snakelets are dropped on the image where they become aligned to the natural wrinkles and curves of a facial image. Step 2 is to confirm the existence of the human face in seven stages by finding facial features of the digital image encompassing the chin, sides of the face, virtual top of the head, eyes, mouth and nose of the image.

Abstract: This is a method for physically-based modeling of three dimensional (3D) general fluid animation in computer graphics. By solving the two dimensional (2D) Navier-Stokes equations using a Computational Fluid Dynamics method, we map it into 3D using the corresponding pressures in the fluid flow field. The method achieves realistic real-time fluid animation by solving the physical governing laws of fluids but avoiding the extensive 3D fluid dynamics computation. Unlike previous computer graphics fluid models, our approach can model many different fluid behaviors by changing the internal or external boundary conditions. It can also model different kinds of fluids by varying the Reynolds number. In addition, we have generated several ways to view the animation of fluid flow field, the streakline of the flow field and the blending of fluids of different colors. Our model can serve as a testbed to simulate many more fluid phenomena which have never been successfully modeled.