Abstract: 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.

Abstract: Embodiments are disclosed that relate to tracking one or more objects during a process that utilizes the objects. For example, one embodiment provides a method for monitoring performance of a process involving one or more objects, wherein the method includes receiving a set of rules defining one or more portions of the process and receiving object identification information regarding the one or more objects. The method further includes, for a selected portion of the process, receiving image information of a physical scene, identifying from the image information and the object identification information an operation performed with an identified object in the physical scene, and taking an action based upon whether the operation satisfies a rule of the set of rules associated with the selected portion of the process.

Abstract: 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.

Abstract: User interface control using a keyboard is described. In an embodiment, a user interface displayed on a display device is controlled using a computer connected to a keyboard. The keyboard has a plurality of alphanumeric keys that can be used for text entry. The computer receives data comprising a sequence of key-presses from the keyboard, and generates for each key-press a physical location on the keyboard. The relative physical locations of the key-presses are compared to calculate a movement path over the keyboard. The movement path describes the path of a user's digit over the keyboard. The movement path is mapped to a sequence of coordinates in the user interface, and the movement of an object displayed in the user interface is controlled in accordance with the sequence of coordinates.

Abstract: 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.

Abstract: User interface control using a keyboard is described. In an embodiment, a user interface displayed on a display device is controlled using a computer connected to a keyboard. The keyboard has a plurality of alphanumeric keys that can be used for text entry. The computer receives data comprising a sequence of key-presses from the keyboard, and generates for each key-press a physical location on the keyboard. The relative physical locations of the key-presses are compared to calculate a movement path over the keyboard. The movement path describes the path of a user's digit over the keyboard. The movement path is mapped to a sequence of coordinates in the user interface, and the movement of an object displayed in the user interface is controlled in accordance with the sequence of coordinates.

Abstract: 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.

Abstract: User interface control using a keyboard is described. In an embodiment, a user interface displayed on a display device is controlled using a computer connected to a keyboard. The keyboard has a plurality of alphanumeric keys that can be used for text entry. The computer receives data comprising a sequence of key-presses from the keyboard, and generates for each key-press a physical location on the keyboard. The relative physical locations of the key-presses are compared to calculate a movement path over the keyboard. The movement path describes the path of a user's digit over the keyboard. The movement path is mapped to a sequence of coordinates in the user interface, and the movement of an object displayed in the user interface is controlled in accordance with the sequence of coordinates.

Abstract: 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.

Abstract: 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.

Abstract: Embodiments are disclosed that relate to tracking one or more objects during a process that utilizes the objects. For example, one embodiment provides a method for monitoring performance of a process involving one or more objects, wherein the method includes receiving a set of rules defining one or more portions of the process and receiving object identification information regarding the one or more objects. The method further includes, for a selected portion of the process, receiving image information of a physical scene, identifying from the image information and the object identification information an operation performed with an identified object in the physical scene, and taking an action based upon whether the operation satisfies a rule of the set of rules associated with the selected portion of the process.

Abstract: 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.

Abstract: A method for constructing an avatar of a human subject includes acquiring a depth map of the subject, obtaining a virtual skeleton of the subject based on the depth map, and harvesting from the virtual skeleton a set of characteristic metrics. Such metrics correspond to distances between predetermined points of the virtual skeleton. In this example method, the characteristic metrics are provided as input to an algorithm trained using machine learning. The algorithm may be trained using a human model in a range of poses, and a range of human models in a single pose, to output a virtual body mesh as a function of the characteristic metrics. The method also includes constructing a virtual head mesh distinct from the virtual body mesh, with facial features resembling those of the subject, and connecting the virtual body mesh to the virtual head mesh.

Abstract: Learning image processing tasks from scene reconstructions is described where the tasks may include but are not limited to: image de-noising, image in-painting, optical flow detection, interest point detection. In various embodiments training data is generated from a 2 or higher dimensional reconstruction of a scene and from empirical images of the same scene. In an example a machine learning system learns at least one parameter of a function for performing the image processing task by using the training data. In an example, the machine learning system comprises a random decision forest. In an example, the scene reconstruction is obtained by moving an image capture apparatus in an environment where the image capture apparatus has an associated dense reconstruction and camera tracking system.

Abstract: A system and method for providing an augmented reality environment in which the environmental mapping process is decoupled from the localization processes performed by one or more mobile devices is described. In some embodiments, an augmented reality system includes a mapping system with independent sensing devices for mapping a particular real-world environment and one or more mobile devices. Each of the one or more mobile devices utilizes a separate asynchronous computing pipeline for localizing the mobile device and rendering virtual objects from a point of view of the mobile device. This distributed approach provides an efficient way for supporting mapping and localization processes for a large number of mobile devices, which are typically constrained by form factor and battery life limitations.

Abstract: 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.

Abstract: 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.

Abstract: A method of modeling a human subject includes receiving from a depth camera a depth map of a scene including the human subject. The human subject is modeled with a virtual skeleton including a plurality of virtual joints. Each virtual joint is defined with a three-dimensional position. Furthermore, each of the plurality of virtual joints is further defined with three orthonormal vectors. The three orthonormal vectors for each virtual joint provide an orientation of that virtual joint at the three-dimensional position defined for that virtual joint.

Abstract: A method for constructing an avatar of a human subject includes acquiring a depth map of the subject, obtaining a virtual skeleton of the subject based on the depth map, and harvesting from the virtual skeleton a set of characteristic metrics. Such metrics correspond to distances between predetermined points of the virtual skeleton. In this example method, the characteristic metrics are provided as input to an algorithm trained using machine learning. The algorithm may be trained using a human model in a range of poses, and a range of human models in a single pose, to output a virtual body mesh as a function of the characteristic metrics. The method also includes constructing a virtual head mesh distinct from the virtual body mesh, with facial features resembling those of the subject, and connecting the virtual body mesh to the virtual head mesh.

Abstract: 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.