| Patent application number | Description | Published |
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| 20090219253 | Interactive Surface Computer with Switchable Diffuser - An interactive surface computer with a switchable diffuser layer is described. The switchable layer has two states: a transparent state and a diffusing state. When it is in its diffusing state, a digital image is displayed and when the layer is in its transparent state, an image can be captured through the layer. In an embodiment, a projector is used to project the digital image onto the layer in its diffusing state and optical sensors are used for touch detection. | 09-03-2009 |
| 20110085705 | DETECTION OF BODY AND PROPS - A system and method for detecting and tracking targets including body parts and props is described. In one aspect, the disclosed technology acquires one or more depth images, generates one or more classification maps associated with one or more body parts and one or more props, tracks the one or more body parts using a skeletal tracking system, tracks the one or more props using a prop tracking system, and reports metrics regarding the one or more body parts and the one or more props. In some embodiments, feedback may occur between the skeletal tracking system and the prop tracking system. | 04-14-2011 |
| 20110210915 | Human Body Pose Estimation - Techniques for human body pose estimation are disclosed herein. Images such as depth images, silhouette images, or volumetric images may be generated and pixels or voxels of the images may be identified. The techniques may process the pixels or voxels to determine a probability that each pixel or voxel is associated with a segment of a body captured in the image or to determine a three-dimensional representation for each pixel or voxel that is associated with a location on a canonical body. These probabilities or three-dimensional representations may then be utilized along with the images to construct a posed model of the body captured in the image. | 09-01-2011 |
| 20120113140 | Augmented Reality with Direct User Interaction - Augmented reality with direct user interaction is described. In one example, an augmented reality system comprises a user-interaction region, a camera that captures images of an object in the user-interaction region, and a partially transparent display device which combines a virtual environment with a view of the user-interaction region, so that both are visible at the same time to a user. A processor receives the images, tracks the object's movement, calculates a corresponding movement within the virtual environment, and updates the virtual environment based on the corresponding movement. In another example, a method of direct interaction in an augmented reality system comprises generating a virtual representation of the object having the corresponding movement, and updating the virtual environment so that the virtual representation interacts with virtual objects in the virtual environment. From the user's perspective, the object directly interacts with the virtual objects. | 05-10-2012 |
| 20120113223 | User Interaction in Augmented Reality - Techniques for user-interaction in augmented reality are described. In one example, a direct user-interaction method comprises displaying a 3D augmented reality environment having a virtual object and a real first and second object controlled by a user, tracking the position of the objects in 3D using camera images, displaying the virtual object on the first object from the user's viewpoint, and enabling interaction between the second object and the virtual object when the first and second objects are touching. In another example, an augmented reality system comprises a display device that shows an augmented reality environment having a virtual object and a real user's hand, a depth camera that captures depth images of the hand, and a processor. The processor receives the images, tracks the hand pose in six degrees-of-freedom, and enables interaction between the hand and the virtual object. | 05-10-2012 |
| 20120117514 | Three-Dimensional User Interaction - Three-dimensional user interaction is described. In one example, a virtual environment having virtual objects and a virtual representation of a user's hand with digits formed from jointed portions is generated, a point on each digit of the user's hand is tracked, and the virtual representation's digits controlled to correspond to those of the user. An algorithm is used to calculate positions for the jointed portions, and the physical forces acting between the virtual representation and objects are simulated. In another example, an interactive computer graphics system comprises a processor that generates the virtual environment, a display device that displays the virtual objects, and a camera that capture images of the user's hand. The processor uses the images to track the user's digits, computes the algorithm, and controls the display device to update the virtual objects on the display device by simulating the physical forces. | 05-10-2012 |
| 20120139897 | Tabletop Display Providing Multiple Views to Users - A tabletop display providing multiple views to users is described. In an embodiment the display comprises a rotatable view-angle restrictive filter and a display system. The display system displays a sequence of images synchronized with the rotation of the filter to provide multiple views according to viewing angle. These multiple views provide a user with a 3D display or with personalized content which is not visible to a user at a sufficiently different viewing angle. In some embodiments, the display comprises a diffuser layer on which the sequence of images are displayed. In further embodiments, the diffuser is switchable between a diffuse state when images are displayed and a transparent state when imaging beyond the surface can be performed. The device may form part of a tabletop comprising with a touch-sensitive surface. Detected touch events and images captured through the surface may be used to modify the images being displayed. | 06-07-2012 |
| 20120194516 | Three-Dimensional Environment Reconstruction - Three-dimensional environment reconstruction is described. In an example, a 3D model of a real-world environment is generated in a 3D volume made up of voxels stored on a memory device. The model is built from data describing a camera location and orientation, and a depth image with pixels indicating a distance from the camera to a point in the environment. A separate execution thread is assigned to each voxel in a plane of the volume. Each thread uses the camera location and orientation to determine a corresponding depth image location for its associated voxel, determines a factor relating to the distance between the associated voxel and the point in the environment at the corresponding location, and updates a stored value at the associated voxel using the factor. Each thread iterates through an equivalent voxel in the remaining planes of the volume, repeating the process to update the stored value. | 08-02-2012 |
| 20120194517 | Using a Three-Dimensional Environment Model in Gameplay - Use of a 3D environment model in gameplay is described. In an embodiment, a mobile depth camera is used to capture a series of depth images as it is moved around and a dense 3D model of the environment is generated from this series of depth images. This dense 3D model is incorporated within an interactive application, such as a game. The mobile depth camera is then placed in a static position for an interactive phase, which in some examples is gameplay, and the system detects motion of a user within a part of the environment from a second series of depth images captured by the camera. This motion provides a user input to the interactive application, such as a game. In further embodiments, automatic recognition and identification of objects within the 3D model may be performed and these identified objects then change the way that the interactive application operates. | 08-02-2012 |
| 20120194644 | Mobile Camera Localization Using Depth Maps - Mobile camera localization using depth maps is described for robotics, immersive gaming, augmented reality and other applications. In an embodiment a mobile depth camera is tracked in an environment at the same time as a 3D model of the environment is formed using the sensed depth data. In an embodiment, when camera tracking fails, this is detected and the camera is relocalized either by using previously gathered keyframes or in other ways. In an embodiment, loop closures are detected in which the mobile camera revisits a location, by comparing features of a current depth map with the 3D model in real time. In embodiments the detected loop closures are used to improve the consistency and accuracy of the 3D model of the environment. | 08-02-2012 |
| 20120194650 | Reducing Interference Between Multiple Infra-Red Depth Cameras - Systems and methods for reducing interference between multiple infra-red depth cameras are described. In an embodiment, the system comprises multiple infra-red sources, each of which projects a structured light pattern into the environment. A controller is used to control the sources in order to reduce the interference caused by overlapping light patterns. Various methods are described including: cycling between the different sources, where the cycle used may be fixed or may change dynamically based on the scene detected using the cameras; setting the wavelength of each source so that overlapping patterns are at different wavelengths; moving source-camera pairs in independent motion patterns; and adjusting the shape of the projected light patterns to minimize overlap. These methods may also be combined in any way. In another embodiment, the system comprises a single source and a mirror system is used to cast the projected structured light pattern around the environment. | 08-02-2012 |
| 20120195471 | Moving Object Segmentation Using Depth Images - Moving object segmentation using depth images is described. In an example, a moving object is segmented from the background of a depth image of a scene received from a mobile depth camera. A previous depth image of the scene is retrieved, and compared to the current depth image using an iterative closest point algorithm. The iterative closest point algorithm includes a determination of a set of points that correspond between the current depth image and the previous depth image. During the determination of the set of points, one or more outlying points are detected that do not correspond between the two depth images, and the image elements at these outlying points are labeled as belonging to the moving object. In examples, the iterative closest point algorithm is executed as part of an algorithm for tracking the mobile depth camera, and hence the segmentation does not add substantial additional computational complexity. | 08-02-2012 |
| 20120196679 | Real-Time Camera Tracking Using Depth Maps - Real-time camera tracking using depth maps is described. In an embodiment depth map frames are captured by a mobile depth camera at over 20 frames per second and used to dynamically update in real-time a set of registration parameters which specify how the mobile depth camera has moved. In examples the real-time camera tracking output is used for computer game applications and robotics. In an example, an iterative closest point process is used with projective data association and a point-to-plane error metric in order to compute the updated registration parameters. In an example, a graphics processing unit (GPU) implementation is used to optimize the error metric in real-time. In some embodiments, a dense 3D model of the mobile camera environment is used. | 08-02-2012 |
| 20120306876 | GENERATING COMPUTER MODELS OF 3D OBJECTS - Generating computer models of 3D objects is described. In one example, depth images of an object captured by a substantially static depth camera are used to generate the model, which is stored in a memory device in a three-dimensional volume. Portions of the depth image determined to relate to the background are removed to leave a foreground depth image. The position and orientation of the object in the foreground depth image is tracked by comparison to a preceding depth image, and the foreground depth image is integrated into the volume by using the position and orientation to determine where to add data derived from the foreground depth image into the volume. In examples, the object is hand-rotated by a user before the depth camera. Hands that occlude the object are integrated out of the model as they do not move in sync with the object due to re-gripping. | 12-06-2012 |
