| Patent application number | Description | Published |
|---|
| 20080316214 | PREFIX SUM PASS TO LINEARIZE A-BUFFER STORAGE - The architecture implements A-buffer in hardware by extending hardware to efficiently store a variable amount of data for each pixel. In operation, a prepass is performed to generate the counts of the fragments per pixel in a count buffer, followed by a prefix sum pass on the generated count buffer to calculate locations in a fragment buffer in which to store all the fragments linearly. An index is generated for a given pixel in the prefix sum pass and stored in a location buffer. Access to the pixel fragments is then accomplished using the index. Linear storage of the data allows for a fast rendering pass that stores all the fragments to a memory buffer without needing to look at the contents of the fragments. This is then followed by a resolve pass on the fragment buffer to generate the final image. | 12-25-2008 |
| 20100197390 | POSE TRACKING PIPELINE - A method of tracking a target includes receiving from a source an observed depth image of a scene including the target. Each pixel of the observed depth image is labeled as either a foreground pixel belonging to the target or a background pixel not belonging to the target. Each foreground pixel is labeled with body part information indicating a likelihood that that foreground pixel belongs to one or more body parts of the target. The target is modeled with a skeleton including a plurality of skeletal points, each skeletal point including a three dimensional position derived from body part information of one or more foreground pixels. | 08-05-2010 |
| 20110080336 | Human Tracking System - 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. | 04-07-2011 |
| 20110080475 | Methods And Systems For Determining And Tracking Extremities Of A Target - 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 then be determined. | 04-07-2011 |
| 20110081044 | Systems And Methods For Removing A Background Of An Image - 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. | 04-07-2011 |
| 20110081045 | Systems And Methods For Tracking A Model - 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 model may be adjusted based on a location or position of one or more extremities estimated or determined for a human target in the grid of voxels. The model may also be adjusted based on a default location or position of the model in a default pose such as a T-pose, a DaVinci pose, and/or a natural pose. | 04-07-2011 |
| 20110102438 | Systems And Methods For Processing An Image For Target Tracking - An image such as a depth image of a scene may be received, observed, or captured by a device. The image may then be processed. For example, the image may be downsampled, a shadow, noise, and/or a missing potion in the image may be determined, pixels in the image that may be outside a range defined by a capture device associated with the image may be determined, a portion of the image associated with a floor may be detected. Additionally, a target in the image may be determined and scanned. A refined image may then be rendered based on the processed image. The refined image may then be processed to, for example, track a user. | 05-05-2011 |
| 20110150271 | MOTION DETECTION USING DEPTH IMAGES - 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. For example, a video game system will update the position of images displayed in the video based on the new positions of the objects. In one implementation, avatars can be moved based on movement of the user in front of a camera. | 06-23-2011 |
