Graphics system using sample tags for blur

• US 6,426,755 B1
• Filed: 05/16/2000
• Issued: 07/30/2002
• Est. Priority Date: 05/16/2000
• Status: Expired due to Term

• Current Assignee: Oracle America, Inc. (Oracle Corporation)
• Original Assignee: Sun Microsystems Incorporated (Oracle Corporation)
• Inventors: Deering, Michael F.
• Primary Examiner(s): Zimmerman, Mark
• Assistant Examiner(s): Nguyen, Kimbinh T.
• Application Number:
  US09/571,768
• Time in Patent Office: 805 Days
• Field of Search: 345/429, 345/581, 345/611, 345/419, 345/582, 345/612, 345/606, 345/422, 345/426, 345/502, 345/616, 382/173, 382/264
• US Class Current: 345/581
• CPC Class Codes: G06T 11/40 Filling a planar surface by adding surface attributes, e.g. colour or texture
• CPC Class Codes: G06T 15/503 Blending, e.g. for anti-aliasing
• CPC Class Codes: H04N 13/122 Improving the 3D impression of stereoscopic images by modifying image signal contents, e.g. by filtering or adding monoscopic depth cues H04N13/128 takes precedence
• CPC Class Codes: H04N 13/257 Colour aspects
• CPC Class Codes: H04N 13/279 the virtual viewpoint locations being selected by the viewers or determined by tracking
• CPC Class Codes: H04N 13/289 Switching between monoscopic and stereoscopic modes
• CPC Class Codes: H04N 13/366 using viewer tracking
• CPC Class Codes: H04N 13/383 for tracking with gaze detection, i.e. detecting the lines of sight of the viewer's eyes

Abstract

A graphics system and method for performing blur effects, including motion blur and depth of field effects, are disclosed. In one embodiment the system comprises a graphics processor, a sample buffer, and a sample-to-pixel calculation unit. The graphics processor is configured to receive a set of three-dimensional (3D) graphics data and render a plurality of samples based on the set of 3D graphics data. The processor is also configured to generate sample tags for the samples, wherein the sample tags are indicative of whether or not the samples are to be blurred. The super-sampled sample buffer is coupled to receive and store the samples from the graphics processor. The sample-to-pixel calculation unit is coupled to receive and filter the samples from the super-sampled sample buffer to generate output pixels, which in turn are displayable to form an image on a display device. The sample-to-pixel calculation units are configured to select the filter attributes used to filter the samples into output pixels based on the sample tags.

Claims

1. A graphics system comprising:

one or more graphics processors configured to receive a set of three-dimensional (3D) graphics data and render a plurality of samples based on the set of 3D graphics data, wherein the graphics processors are configured to generate sample tags for the samples, wherein the sample tags are indicative of whether or not the samples are to be blurred;

a super-sampled sample buffer coupled to receive and store the plurality of samples from the graphics processor; and

one or more sample-to-pixel calculation units coupled to receive and filter the samples from the super-sampled sample buffer to generate output pixels, wherein the output pixels are displayable to form an image on a display device, and wherein the sample-to-pixel calculation units are configured to select the filter attributes used to filter the samples into output pixels based on the sample tags.

2. The graphics system as recited in claim 1, wherein the sample-to-pixel calculation units filter the samples in real-time and convey the output pixels to a display device without storing the output pixels in an intervening frame buffer.

3. The graphics system as recited in claim 1, wherein the filter attributes include the filter'"'"'s extent.

4. The graphics system as recited in claim 1, wherein the filter attributes include the filter'"'"'s radius.

5. The graphics system as recited in claim 1, wherein the filter attributes include the filter'"'"'s shape.

6. The graphics system as recited in claim 1, wherein the filter attributes include directional orientation of the filter.

7. The graphics system as recited in claim 1, wherein the filter attributes include the filter type.

8. The graphics system as recited in claim 1, wherein the sample-to-pixel calculation units are configured to select either a circular filter or an elliptical filter based on the sample tags.

9. The graphics system as recited in claim 8, wherein the sample-to-pixel calculation units are configured to select the orientation of the elliptical filter based on the sample tags.

10. The graphics system as recited in claim 1, wherein the filter attributes include the distance from the center of the filter beyond which samples no longer contribute.

11. The graphics system as recited in claim 1, wherein the filter attributes include the number of samples to be filtered per pixel.

12. The graphics system as recited in claim 1, wherein the filter attributes include the maximum number of samples to be filtered per pixel.

13. The graphics system as recited in claim 1, wherein the filter attributes include the minimum number of samples to be filtered per pixel.

14. The graphics system as recited in claim 1, wherein the sample-to-pixel calculation units are configured to select the filter attributes used to filter the samples on a pixel-by-pixel basis based on the sample tags that correspond to the samples being filtered for each particular output pixel.

15. The graphics system as recited in claim 1, wherein the sample-to-pixel calculation units are configured to select the filter attributes used to filter the samples into output pixels based on the sample tags that correspond to the samples that are closest to the center of the filter.

16. The graphics system as recited in claim 1, wherein the sample-to-pixel calculation units are configured to select the filter attributes used to filter the samples into output pixels based on the most prevalent sample tag for each set of samples being filtered to form each particular output pixel.

17. The graphics system as recited in claim 1, wherein the samples are stored in the sample buffer according to bins, wherein the sample-to-pixel calculation units are configured to select a first filter radius when no samples with tags that indicate high levels of blur within any of the bins that contain potential samples for a particular output pixel, wherein the sample-to-pixel calculation units are configured to select a second filter radius when there are samples with tags that indicate high levels of blur within one or more of the bins that contain potential samples for a particular output pixel, wherein the second filter radius is greater than the first filter radius.

18. The graphics system as recited in claim 1, wherein the tags are stored in the sample buffer in lieu of alpha information.

19. The graphics system as recited in claim 1, wherein the graphics processor is configured to calculate which filter attributes will result in a desired final image based on the 3D graphics data.

20. A graphics system comprising:

a means for receiving a set of three-dimensional (3D) graphics data and rendering a plurality of samples based on the set of 3D graphics data, wherein the means for receiving and rendering is configured to generate sample tags for the samples, wherein the sample tags are indicative of whether or not the samples are to be blurred;

a sample buffer coupled to receive and store the plurality of rendered samples; and

a means for calculating pixels from samples, wherein the means for calculating is coupled to receive and filter samples from the sample buffer to generate output pixels, wherein the output pixels are displayable to form an image on a display device, and wherein the means for calculating is configured to select the filter attributes used to filter the samples into output pixels based on the sample tags.

21. A method for rendering a set of 3D graphics data, the method comprising:

rendering a plurality of samples based on the 3D graphics data;

generating tags for the samples, wherein the tags are indicative of the samples'"'"' blurriness;

storing the rendered samples and tags into a sample buffer;

selecting a set of stored samples to be filtered;

selecting filter attributes based on the selected samples'"'"' tags; and

filtering the selected samples to form output pixels using the selected filter attributes, wherein the output pixels are displayable to form an image based on the 3D graphics data.

22. The method as recited in claim 21, wherein the output pixels are output without being stored into a frame buffer.

23. The method as recited in claim 21, wherein the filtering is performed in real-time.

24. The method as recited in claim 21, wherein the filter attributes include the filter'"'"'s extent.

25. The method as recited in claim 21, wherein the filter attributes include the filter'"'"'s radius.

26. The method as recited in claim 21, wherein the filter attributes include the filter'"'"'s shape.

27. The method as recited in claim 21, wherein the filter attributes include directional orientation of the filter.

28. The method as recited in claim 21, wherein the filter attributes include the filter type.

29. The method as recited in claim 21, wherein the filter attributes include the distance from the center of the filter beyond which samples no longer contribute.

30. The method as recited in claim 21, wherein the filter attributes include the number of samples to be filtered per pixel.

31. The method as recited in claim 21, wherein the filter attributes include the maximum number of samples to be filtered per pixel.

32. The method as recited in claim 21, wherein the filter attributes include the minimum number of samples to be filtered per pixel.

33. The method as recited in claim 21, wherein said selecting filter attributes is performed on a pixel-by-pixel basis based on the sample tags that correspond to the set of samples being filtered for each particular output pixel.

34. The method as recited in claim 21, wherein said selecting filter attributes is performed based on the sample tags that correspond to the samples that are closest to the center of the filter.

35. The method as recited in claim 21, wherein said selecting filter attributes is performed based on the most prevalent sample tag for the set of samples selected for each particular output pixel.

36. The method as recited in claim 21, wherein the tags are stored in the sample buffer in an area of the sample buffer that is reserved for alpha information.

37. The method as recited in claim 21, wherein the tags encode filter attribute information to implement one or more of the following effects:

motion blur, depth of field effects, and ripple effects.

38. The graphics system as recited in claim 21, wherein the tags encode filter attribute information to implement one or more of the following effects:

motion blur, depth of field effects, and ripple effects.

39. The method as recited in claim 21, wherein the samples are stored in the sample buffer according to bins, wherein said selecting filter attributes comprises selecting a first filter radius when there are no samples that have tags that indicate high levels of blur within any of the bins that contain the set of selected samples for a particular output pixel, and wherein said selecting filter attributes comprises selecting a second filter radius when there are samples that have tags that indicate high levels of blur within one or more of the bins that contain the set of selected samples for a particular output pixel, wherein the second filter radius is greater than the first filter radius.

40. A method for rendering 3D graphics data, the method comprising:

detecting which objects in the 3D graphics data are moving more than a predetermined threshold amount relative to a viewer'"'"'s retina;

rendering samples corresponding to the detected moving objects and non-moving objects into a sample buffer, wherein the samples corresponding to the moving objects are tagged to indicate that motion blurring is to be performed; and

filtering the samples to form output pixels, wherein the output pixels are usable to form an image on a display device, wherein said filtering comprises using a first filter for samples without tags and a second filter for samples with tags.

41. The method as recited in claim 40, wherein said rendering comprises tagging the samples corresponding to the moving objects with a multiple-bit tag, wherein the multiple-bit tag is indicative of the amount of blur that is to be applied to the sample.

42. The method as recited in claim 40, wherein said rendering comprises tagging the samples corresponding to the moving objects with a multiple-bit tag, wherein the multiple-bit tag is indicative of one of a plurality of different filters to be applied to the sample.

43. The method as recited in claim 40, wherein the first filter has a larger radius than the second filter.

44. The method as recited in claim 40, wherein the first filter has a larger extent than the second filter.

45. The method as recited in claim 40, wherein the first filter is a lower band pass filter than the second filter.

46. The method as recited in claim 40, wherein the first filter is selected to the moving objects to appear more perceptually blurred than non-moving objects filtered using the second filter.

47. The method as recited in claim 40, further comprising:

normalizing the samples corresponding moving objects; and

normalizing the output pixels.

48. A method for rendering 3D graphics data, the method comprising:

receiving a set of compressed graphics data;

decompressing the graphics data;

detecting which objects are to be blurred;

rendering samples corresponding to blurred and non-blurred objects into a sample buffer, wherein the samples corresponding to moving objects are tagged to indicate that are to be blurred; and

filtering the samples to form an output pixel by;

calculating the distance from the center of output pixel to each sample;

using the calculated distance to index into a table of pre-computed contribution factors for samples corresponding to non-blurred objects; and

using a fraction of the calculated distance to index into a table of pre-computed contribution factors for samples corresponding to blurred objects.

49. The method as recited in claim 48, further comprising:

normalizing the samples corresponding moving objects; and

normalizing the output pixels.