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103 results about "Texture memory" patented technology

Texture memory is a type of digital storage that makes texture data readily available to video rendering processors (also known as GPUs), typically 3D graphics hardware. It is most often (but not always) implemented as specialized RAM (TRAM) that is designed for rapid reading and writing, enabling the graphics hardware increased performance in rendering 3D imagery.

Synchronizing graphics texture management in a computer system using threads

InactiveUS6437788B1Improved context-switchingRemoval is very complexResource allocationCathode-ray tube indicatorsGraphicsOperational system
A computer system having a graphics display with texture management employs a graphics adapter with texture memory. The graphics adapter is "virtualized' by the operating system. When making a graphics context switch, the state of the graphics adapter including texture memory is saved. Threads are used to allow rapid and frequent context switches. A graphics process that will use texture memory in the adapter reserves a thread, for use during a graphics context switch. The thread calls into the operating system where it is blocked until a graphics context switch is initiated. At that time, the thread is unblocked to do texture management, such as saving of texture memory. During the save portion of the graphics context switch the graphics driver saves the current hardware state of the adapter, and the special purpose texture thread is unblocked to allow texture memory to be processed, and saves texture memory and calls back into the driver where it is blocked. During the restore portion of the graphics context switch the driver restores the state of the adapter to that of another graphics process, except for texture memory. The special purpose texture thread associated with the new graphics process is unblocked, passed an indication that a restore operation is in progress, and restores textures as required and calls back into the driver where it is blocked in the kernel. The driver completes the context switch and the graphics process is dispatched.
Owner:NVIDIA CORP

Body drafting visual method based on surface sample-taking

The invention relates to a volume rendering visualization method based on the sampling. Firstly convert the volume data into 3D texture memory; then design a bounding box containing all the volume data with the rectangular coordinate system origin as the center, set the initial corresponding relation of 8 vertex coordinates and color values to have the bounding box rotating around the center and calculate the new coordinates of the bounding box after rotating by the self-defined rotation matrix; after point coordinates inverse rotation and linear transformation to the intersection points of the cutting plane perpendicular to the line of sight and the edges of the bounding box to get the corresponding color values, color convex polygon sampling plane can be obtained through GPU trilinear interpolation calculation; with the color value of each point of the sampling plane as the coordinate, the 3D texture volume data can be sampled to perform the color composition calculation; change the step value to have the cutting plane advancing along the light of sight until the cutting plane does not intersect with the bounding box and draw the final image. The method calculates large amounts of sampling coordinates point of the polygon sampling plane at one time, thus improving the program parallelism, reducing the workload and improving volume rendering speed remarkably.
Owner:GUILIN UNIV OF ELECTRONIC TECH

Alternative hough forests real time target tracking method based on GPU (graphics process unit)

An alternative hough forests real time target tracking method based on a GPU (graphics process unit) is provided. The alternative hough forests real time target tracking method based on the GPU comprises: 1) extracting a training sample set according to a video sequence to be tested; 2) setting the number of random trees in the alternative hough forests and the maximum depth of the forests; 3) giving the training samples different weights; 4) initializing root nodes of each random tree; 5) building the alternative hough forests; 6) employing a splitting strategy when the nodes are splitting; 7) storing the alternative hough forests into a texture memory of the GPU; 8) manually determining an object region and an object center of a first frame image in a video, and setting a search radius; 9) detecting a follow-up frame through employing built alternative hough forests in the GPU, and obtaining a confidence map with respect to the object center position; 10) storing the confidence map into the texture memory of the GPU; 11) determining the object position in the present frame through employing the confidence map and combining the object region and the object center of the last frame; and 12) repeating the step 9 and the step 10 until completing the object tracking of all the frames in the video sequence.
Owner:XIAMEN UNIV
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