Abstract: An electronic device (100) includes a first imaging camera (116) and a second imaging camera (114) disposed at a first surface (106). The first imaging camera (116) has a first angle of view and the second imaging camera (114) has a second angle of view greater than the first angle of view. The electronic device (100) further includes a depth sensor (120) disposed at the first surface (106). The depth sensor can include a modulated light projector (119) to project a modulated light pattern (500) and at least one of the first imaging camera (116) and the second imaging camera (114) to capture a reflection of the modulated light pattern (500). The electronic device (100) further can include a third imaging camera (118) disposed at a second surface (104).

Abstract: An electronic device (100) includes a first processor (802) and a second processor (804) coupled to the first processor. The first processor (802) is to receive image data from a first imaging camera (114, 116) and to determine two-dimensional (2D) spatial feature data representing one or more 2D spatial features identified from the image data. The second processor (804) is to determine three-dimensional (3D) spatial feature data representing one or more 3D spatial features identified based on the 2D spatial feature data. Further, the first processor (802) can initiate detection of one or more 2D spatial features from a portion of an image frame prior to receiving the entire image frame.

Abstract: An electronic device (100) includes a depth sensor (120), a first imaging camera (114, 116), and a controller (802). The depth sensor (120) includes a modulated light projector (119) to project a modulated light pattern (500). The first imaging camera (114, 116) is to capture at least a reflection of the modulated light pattern (500). The controller (802) is to selectively modify (1004) at least one of a frequency, an intensity, and a duration of projections of the modulated light pattern by the modulated light projector responsive to at least one trigger event (1002). The trigger event can include, for example, a change (1092) in ambient light incident on the electronic device, detection (1094) of motion of the electronic device, or a determination (1096) that the electronic device has encountered a previously-unencountered environment.

Abstract: Systems, methods and computer readable media are disclosed for controlling perspective of a camera-controlled computer. A capture device captures user gestures and sends corresponding data to a recognizer engine. The recognizer engine analyzes the data with a plurality of filters, each filter corresponding to a gesture. Based on the output of those filters, a perspective control is determined, and a display device displays a new perspective corresponding to the perspective control.

Abstract: An improvement to a roadside sprayer fixates spray nozzles on a registration plate. The registration plate may include integral tabs depending on the application. Inclination of the tabs is adjustable to place streams and droplets in a desired swath coverage. With the nozzles rigidly mounted onto the plate, the entire plate is nutated. The use of the registration plate in a spray unit creates a uniform nutation among the nozzles, thereby reducing variability in droplet placement, and providing a more predictable spray from the nozzles. In other embodiments, the spray unit is utilized in a spray system adaptable to service vehicles, and may be utilized in conjunction with a vegetation engagement device, such as a cutter to engage multiple zones of a roadway right-of-way. Additionally, an improved spray unit includes an electromagnetic field and an attractor to generate plate motion.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may then be discarded to isolate one or more voxels associated with a foreground object such as a human target and the isolated voxels associated with the foreground object may be processed.

Abstract: A method of tracking a subject includes receiving from a source a depth image of a scene including the subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that image the subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the subject as a model including a plurality of shapes.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.

Abstract: Systems, methods and computer readable media are disclosed for controlling perspective of a camera-controlled computer. A capture device captures user gestures and sends corresponding data to a recognizer engine. The recognizer engine analyzes the data with a plurality of filters, each filter corresponding to a gesture. Based on the output of those filters, a perspective control is determined, and a display device displays a new perspective corresponding to the perspective control.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may then be discarded to isolate one or more voxels associated with a foreground object such as a human target and the isolated voxels associated with the foreground object may be processed.

Abstract: A method of tracking a target includes receiving from a source a depth image of a scene including the human subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that belong to the human subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of shapes.

Abstract: A sensor system creates a sequence of depth images that are used to detect and track motion of objects within range of the sensor system. A reference image is created and updated based on a moving average (or other function) of a set of depth images. A new depth images is compared to the reference image to create a motion image, which is an image file (or other data structure) with data representing motion. The new depth image is also used to update the reference image. The data in the motion image is grouped and associated with one or more objects being tracked. The tracking of the objects is updated by the grouped data in the motion image. The new positions of the objects are used to update an application.

Abstract: A display panel for use with a multi-panel display. The display panel includes a display panel including an array of display pixels disposed surrounded by a bezel, the array of display pixels for emitting a display image having a first size, and an optical expansion layer disposed over the array of display pixels to magnify the display image to appear to have a second size larger than the first size and to at least partially conceal the bezel surrounding the housing. The optical expansion layer includes a first array of microlenses optically coupled to the array of display pixels to cause light from the display pixels to diverge, a second array of microlenses having complementary optical power to the first array of microlenses; and an optically transparent offset layer disposed between the first and second arrays of microlenses. Other embodiments are disclosed and claimed.

Abstract: A display panel for use with a multi-panel display includes an array of display pixels to emit pixel light. A fiber bundle including an array of fibers is disposed over the array of display pixels. The fiber bundle includes a first end of the array of fibers rigidly fixed adjacent to the array of display pixels and optically aligned with the array of display pixels and a loose fiber portion that permits a second end of the array of fibers opposite the first end to slump-over and move. The fiber bundle receives the pixel light emitted from the array of display pixels into the first end of the array of fibers and emits the pixel light out the second end of the array of fibers.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.

Abstract: A method of tracking a target includes receiving from a source a depth image of a scene including the human subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that belong to the human subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of shapes.

Abstract: A method of tracking a target includes receiving from a source a depth image of a scene including the human subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that belong to the human subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of shapes.

Abstract: An image such as a depth image of a scene may be received, observed, or captured by a device. A grid of voxels may then be generated based on the depth image such that the depth image may be downsampled. A background included in the grid of voxels may also be removed to isolate one or more voxels associated with a foreground object such as a human target. A location or position of one or more extremities of the isolated human target may be determined and a model may be adjusted based on the location or position of the one or more extremities.

Abstract: A method of tracking a target includes receiving from a source a depth image of a scene including the human subject. The depth image includes a depth for each of a plurality of pixels. The method further includes identifying pixels of the depth image that belong to the human subject and deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of shapes.