DETAILED ACTION
This action is responsive to the Amendments and Remarks received 03/04/2026 in which claims 2–4, 19, 21, and 22 are cancelled, claims 1, 18, 20, and 25 are amended, and no claims are added as new claims.
Response to Arguments
Examiner does not acquiesce regarding Applicant’s alleged deficiencies of Williams and Salmani Rahimi. Examiner incorporates herein previous Responses to Arguments.
On pages 9–10 of the Remarks, Applicant contends the combination of Williams and Salmani Rahimi fails to teach or suggest the feature added by way of amendment. Examiner finds the arguments moot in view of the new grounds of rejection necessitated by amendment. Specifically, the additional teachings of Hunt are used to teach or suggest the amended features of representative claim 1 drawn to a rolling shutter camera and the capturing of an image line-by-line. For example, Hunt teaches that for a rolling shutter scenario, a movement can create a smearing effect from one rendered line to the next and teaches compensating for the movement by taking account of the shutter rate of the camera and the user’s movement to adjust the next rendered line accordingly. These teachings of Hunt are viewed equivalent to Applicant’s disclosure at paragraph [0061] of the published Specification. See rejections under 35 U.S.C. 103, infra.
Other claims are not argued separately. Remarks, 10–11.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 5–8, 10, 11, 14, 16–18, 20, and 23–26 are rejected under 35 U.S.C. 103 as being unpatentable over Williams (US 9,514,571 B2), Salmani Rahimi (US 11,335,077 B1), and Hunt (US 11,176,901 B1).
Examiner interprets this application as using a well-known solution to the problem of display latency in VR/AR/XR head-mounted displays (HMDs). HMDs utilize head pose information to generate a real-time, realistic environment to a user. When a user moves his head or pans or tilts his head, the rendered images move accordingly to present a realistic environment to the user. Conventionally, the user’s head pose is input into a rendering engine that constructs image frames based on the pose information at a particular frame rate. However, because rendering is computationally intensive, there is often a noticeable-to-the-user lag/latency between the input of the pose information and the final output display of the rendered image during which time the user’s head could be slightly different than the pose used to compute the frame. Therefore, the display frame is somewhat out-of-date, which is bothersome to the user. To compensate for this, the prior art, as demonstrated by the plethora of publications listed under the Conclusion Section of this Office Action, recognized that although the rendered frame may be out-of-date with respect to the most current pose information, the rendered frame can be adjusted quickly with a warping function (pixel-wise warping computations are relatively quick and can be performed to make minor adjustments to the output frame just prior to outputting the frame for display) to compensate for the relatively small difference between the out-of-date pose used to render the frame and the most up-to-date pose gathered or predicted right before displaying the frame. The prior art conventionally calls this solution, “time warping.” See e.g. Holmes (US 2023/0360227 A1), para. [0080]. See also Parker (US 2017/0180721), ¶ 0012, explaining the problem and characterizing it as “motion-to-photon latency.”
Regarding claim 1, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests a method comprising: at a device including an image sensor, a display, one or more processors, and non-transitory memory, wherein the image sensor is a rolling shutter camera (Williams, Abstract: teaches a head-mounted display (HMD); Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display): predicting, during a prediction time period prior to a capture time and a display time, a capture pose of the device in a physical environment at the capture time and a display pose of the device in the physical environment at the display time (Examiner notes the capture and display time periods can be the same given the delayed display time could also be used as a next capture time since HMDs are capturing and displaying continuously; Williams, Fig. 7A and corresponding description: teaches using a predicted pose for generating a rendered image at capture time (i.e. predicted capture pose) and teaches generating an updated pose estimate that takes into account the first prediction and adjusts the first prediction using updated position/motion information to generate a second predicted pose used at display time; While William’s teachings alone teach or suggest this feature, Salmani Rahimi’s teachings bolster the finding of obviousness; Salmani Rahimi, Claim 2: teaches the predicted pose can be based on motion “prior to when the image of the real environment is captured.”; Williams, Fig. 6A: teaches updated pose information prior to displaying the updated image; Williams, col. 9, ln. 66–col. 10, ln. 2: teaches pose predictions can be obtained by extrapolating from previous movement of the HMD, thus teaching the predictions are decoupled from a capture or display time period), wherein the capture time is defined relative to a capture time period of the rolling shutter camera (Examiner notes Applicant’s published paragraph [0061] explains the capture time period is the number of lines of the image sensor multiplied by the readout time period length of an image line, plus one additional exposure time period representing the time it takes to expose the first line in the image (since the readout line trails the exposure line, the timing calculation must add one additional line’s exposure time for the first line) Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image and furthermore explicitly explains, “For example, if a first horizontal segment is displayed, followed by a second horizontal segment below the first, and the viewer has moved, the image (created by the combined horizontal segments) will appear to smear (e.g., skew, shear, or compress). However, this effect is predictable, based on the known rolling shutter rate and the viewer's movements…”; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display); capturing, using the image sensor, an image of the physical environment during a capture time period including the capture time (Williams, col. 7, ll. 4–22: teaches images of an environment captured for determining pose of an HMD), wherein the capture time period is based on a known hardware timing characteristic of the rolling shutter camera (Hunt, col. 27, ll. 15–39: teaches, “For example, if a first horizontal segment is displayed, followed by a second horizontal segment below the first, and the viewer has moved, the image (created by the combined horizontal segments) will appear to smear (e.g., skew, shear, or compress). However, this effect is predictable, based on the known rolling shutter rate and the viewer's movements…”); generating a warp definition based on the predicted capture pose and the predicted display pose (Williams, col. 7, ll. 23–42: teaches homographic transformations and/or pixel offset adjustments (i.e. warp definitions) calculated based on updated pose information representing the difference between the predicted pose at a rendering time and a predicted updated pose at display time; see also Williams, col. 10, ll. 3–33: teaching the late-stage pose-adjusted images are obtained by applying homographic transformations, affine transform, and/or two-dimensional pixel shifting; Williams does not particularly discuss the transformations as warping, but Salmani Rahimi, col. 7, ll. 33–67: teaches the HMD warping the rendered view by distorting the image to account for changes in pose); warping, using the one or more processors, the image of the physical environment based on the warp definition (Williams, col. 7, ll. 23–42: teaches homographic transformations and/or pixel offset adjustments (i.e. warp definitions) used to solve the latency problem discussed at col. 4, ll. 44–58; Williams, col. 9, ll. 55–61: teaches applying late stage graphical adjustments to pre-rendered images to generate pose-updated images for display; see also Williams, col. 10, ll. 3–33: teaching the late-stage pose-adjusted images are obtained by applying homographic transformations, affine transform, and/or two-dimensional pixel shifting); and displaying, on the display, the warped image of the physical environment during a display time period including the display time (Williams, col. 9, ll. 55–61: teaches applying late stage graphical adjustments to pre-rendered images to generate pose-updated images for display; see also Williams, col. 10, ll. 3–33: teaching the late-stage pose-adjusted images are displayed).
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to combine the elements taught by Williams, with those of Salmani Rahimi, because both references are drawn to the same field of endeavor such that one wishing to practice time warping for an HMD would be led to their relevant teachings, and because Salmani Rahimi is merely teaching the same solution as Williams, but using another art-recognized term to describe a change to a captured image, i.e. warping, to describe the mathematical adjustments made to an image prior to display. Thus, the combination is a mere combination of prior art elements, according to known methods, to yield a predictable result. This rationale applies to all combinations of Williams and Salmani Rahimi used in this Office Action unless otherwise noted.
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to combine the elements taught by Williams and Salmani Rahimi, with those of Hunt, because all three references are drawn to the same field of endeavor such that one wishing to practice time warping for an HMD would be led to their relevant teachings, and because Hunt is merely teaching what was well-known in the art regarding rolling shutter cameras and rolling display using a rolling buffer. Therefore, the skilled artisan would have found it obvious to combine Williams’s teachings regarding rolling buffer output of frames with Hunt’s rolling buffer for outputting frames. Thus, the combination is a mere combination of prior art elements, according to known methods, to yield a predictable result. This rationale applies to all combinations of Williams, Salmani Rahimi, and Hunt used in this Office Action unless otherwise noted.
Regarding claim 5, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein predicting the capture pose and/or the display pose is based on prior motion of the device (Williams, col. 7, ll. 4–22: teaches images of an environment captured for determining predicted pose of an HMD; Williams, col. 17, ll. 6–15: teaches predicted and updated pose information can be determined using a combination of camera-based pose tracking information and low-latency IMU motion information; Williams, col. 9, ll. 42–44: teaches pose prediction may use movement history of the HMD; Williams, col. 9, ln. 66–col. 10, ln. 2: teaches pose predictions can be obtained by extrapolating from previous movement of the HMD).
Regarding claim 6, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein predicting the capture pose and/or the display pose is based on content displayed on the display (Williams, col. 17, ll. 6–15: teaches predicted and updated pose information can be determined using a combination of camera-based pose tracking information and low-latency IMU motion information; Salmani Rahimi, col. 2, ll. 1–15: teaches pose predictions can be based on predicting object movements within the image (i.e. displayed content)).
Regarding claim 7, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein predicting the capture pose includes determining the capture time (Williams, Figs. 6A and 7A: teach the first predicted pose is the pose at capture time just prior to rendering the AR image).
Regarding claim 8, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 7, wherein determining the capture time includes determining the middle of the capture time period (Williams, Fig. 7A and col. 18, ll. 31–36: teaches a middle display time for generating a predicted display pose; While Williams teaches using the middle time for display, the skilled artisan understands that given latency between capture and display and the frame rate of such HMD systems, the display time also corresponds to a next capture time such that the updated predicted display pose could also be the predicted capture pose for the next capture time period; see also Williams, col. 7, ll. 23–41: teaches “predicted poses at the rendering frame rate” (i.e. the capturing timing); Salmani Rahimi, col. 15, ll. 64–67: teaches pose “prediction can be conducted at any known time interval to correspond with the rate of image capture.”).
Regarding claim 10, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein predicting the display pose includes determining the display time (Williams, Fig. 7A and col. 18, ll. 31–36: teaches a middle display time for generating a predicted display pose; Examiner notes that in order to find a middle display time, a display time determination must be made).
Regarding claim 11, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 10, wherein determining the display time includes determining the middle of the display time period (Williams, Fig. 7A and col. 18, ll. 31–36: teaches a middle display time for generating a predicted display pose).
Regarding claim 14, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein generating the warp definition is performed prior to the capture time period (Salmani Rahimi, Claim 2: teaches the predicted pose can be based on motion “prior to when the image of the real environment is captured.”; see also William’s teachings regarding predicted pose from historic data).
Regarding claim 16, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein the warp definition is further based on a predicted motion of the device during the capture time period (Williams, col. 7, ll. 4–22: teaches images of an environment captured for determining predicted pose of an HMD; Williams, col. 17, ll. 6–15: teaches predicted and updated pose information can be determined using a combination of camera-based pose tracking information and low-latency IMU motion information; Williams, col. 9, ll. 42–44: teaches pose prediction may use movement history of the HMD; Williams, col. 9, ln. 66–col. 10, ln. 2: teaches pose predictions can be obtained by extrapolating from previous movement of the HMD).
Regarding claim 17, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein the warp definition is further based on a predicted motion of the device during the display time period (Williams, col. 7, ll. 4–22: teaches images of an environment captured for determining predicted pose of an HMD; Williams, col. 17, ll. 6–15: teaches predicted and updated pose information can be determined using a combination of camera-based pose tracking information and low-latency IMU motion information; Williams, col. 9, ll. 42–44: teaches pose prediction may use movement history of the HMD; Williams, col. 9, ln. 66–col. 10, ln. 2: teaches pose predictions can be obtained by extrapolating from previous movement of the HMD).
Claim 18 lists the same elements as claim 1, but is drawn to an apparatus rather than a method. Therefore, the rationale for the rejection of claim 1 applies to the instant claim.
Claim 20 lists the same elements as claim 1, but is drawn to a CRM rather than a method. Therefore, the rationale for the rejection of claim 1 applies to the instant claim.
Regarding claim 23, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein warping the image of the physical environment is initiated before capturing the image of the physical environment is completed (Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display).
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to combine the elements taught by Williams and Salmani Rahimi, with those of Hunt, because all three references are drawn to the same field of endeavor such that one wishing to practice time warping for an HMD would be led to their relevant teachings, and because Hunt is merely teaching what was well-known in the art regarding rolling shutter cameras and rolling display using a rolling buffer. Therefore, the skilled artisan would have found it obvious to combine Williams’s teachings regarding rolling buffer output of frames with Hunt’s rolling buffer for outputting frames. Thus, the combination is a mere combination of prior art elements, according to known methods, to yield a predictable result. This rationale applies to all combinations of Williams, Salmani Rahimi, and Hunt used in this Office Action unless otherwise noted.
Regarding claim 24, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein displaying the warped image of the physical environment is initiated before warping of the image of the physical environment is completed (Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display).
Regarding claim 25, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 1, wherein the rolling shutter camera captures a first portion of the image of the physical environment during a first portion of the capture time period and captures a second portion of the image of the physical environment during a second portion of the capture time period and warping the first portion of the image of the physical environment is initiated before capturing of the second portion of the image of the physical environment is completed (Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display).
Regarding claim 26, the combination of Williams, Salmani Rahimi, and Hunt teaches or suggests the method of claim 25, wherein the display is a rolling display camera that displays a first portion of the warped image during a first portion of the display time period and displays a second portion of the warped image during a second portion of the display time period and displaying the first portion of the warped imaged is initiated before warping of the second portion of the image of the physical environment is completed (Examiner notes rolling display and rolling cameras are the most prevalent embodiment as of Applicant’s filing date such that such properties of such devices (e.g. everyone’s camera phone) cannot be found to be a nonobvious feature; Hunt, col. 27, ll. 15–39: teaches, in an HMD implementation, rolling display of frame segments captured by a rolling shutter camera system wherein the rolling display is accomplished by rendering segments of an image prior to completion of the capturing of the image; see also Hunt, col. 26, ll. 21–32: teaches the rendering pipeline utilizing a rolling buffer for outputting rendered frames for display).
Claims 9 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Williams, Salmani Rahimi, Hunt, and PI (US 2022/0237814 A1).
Regarding claim 9, the combination of Williams, Salmani Rahimi, Hunt, and PI teaches or suggests the method of claim 7, wherein determining the capture time is based on a prediction confidence (PI, Abstract and ¶ 0014: teaches correlating prediction confidence with time points to optimize pose estimation).
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to combine the elements taught by Williams, Salmani Rahimi, and Hunt, with those of PI, because all four references are drawn to the same field of endeavor such that one wishing to practice pose estimation for an HMD would be led to their relevant teachings, and because PI is merely teaching that improving pose estimation using confidence values to rank poses captured at distinct times and help optimize predicted 3D pose. Thus, the combination is a mere combination of prior art elements, according to known methods, to yield a predictable result. This rationale applies to all combinations of Williams, Salmani Rahimi, Hunt, and PI used in this Office Action unless otherwise noted.
Regarding claim 12, the combination of Williams, Salmani Rahimi, Hunt, and PI teaches or suggests the method of claim 10, wherein determining the display time is based on a prediction confidence (PI, Abstract and ¶ 0014: teaches correlating prediction confidence with time points to optimize pose estimation).
Claims 13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Williams, Salmani Rahimi, Hunt, and Holmes (US 2023/0360227 A1).
Regarding claim 13, the combination of Williams, Salmani Rahimi, Hunt, and Holmes teaches or suggests the method of claim 1, wherein the warp definition includes a warp mesh (Holmes, ¶ 0105: teaches time warping can involve distortion by distorting a mesh to create a geometric transform).
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have been motivated to combine the elements taught by Williams , Salmani Rahimi, and Hunt, with those of Holmes, because all four references are drawn to the same field of endeavor such that one wishing to practice time warping for an HMD would be led to their relevant teachings, and because Holmes is merely teaching what is well-known in the art regarding a distortion or warping of an image being accomplished using a distortion mesh or warp mesh. Thus, the combination is a mere combination of prior art elements, according to known methods, to yield a predictable result. This rationale applies to all combinations of Williams, Salmani Rahimi, Hunt, and Holmes used in this Office Action unless otherwise noted.
Regarding claim 15, the combination of Williams, Salmani Rahimi, Hunt, and Holmes teaches or suggests the method of claim 1, wherein the warp definition is further based on a depth map including a plurality of depths respectively associated with a plurality of pixels of the image of the physical environment (Holmes, ¶ 0127: teaches a mesh render with depth information can be used to effectuate the geometric transform).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Goodman (US 2023/0009367 A1) teaches warping a display image prior to presentation to the user of an HMD using distortion meshes (¶ 0066) and teaches predicting future poses of content in the images using motion or translation vectors (¶ 0035).
Le (US 2024/0013441 A1) teaches warping a camera motion compensated frame using optical flow information and a latent representation of a depth map (¶ 0168), wherein both camera motion compensation and object motion compensation are used for HMD (Title).
Ajaykumar (US 2023/0393650 A1) teaches HMD motion prediction to estimate future head pose to account for delay (¶ 0083) and a pose prediction engine that predicts a pose based on existing pose prediction and updated prediction time which takes into account movement between a past pose and a future pose (¶¶ 0096 and 0103).
Holmes (US 2023/0360227 A1) teaches warping or reprojecting a rendered frame before sending it to a display and can use a first time when a first frame is captured to obtain a pose and can compensate for movement of the XR system using a time warp process to estimate a future pose of the XR system (¶¶ 0080, 0083, 0084, 0090).
Parker (US 2017/0180721 A1) teaches compensating for rendering and display latency by predicting potential future poses of the display device including interpolating predicted poses for use in matching with actual poses (¶¶ 0018 and 0019), using motion parameter information and time span information (¶ 0031), wherein probability distributions include confidence scores (¶ 0032).
Choudhuri (US 2020/0364901 A1) teaches computing predicted poses of an HMD using motion parameters and communication latency time periods (¶ 0011), wherein confidence scores are used to rank pose estimations (¶ 0101) and motion of device is used to predict a future pose at a future time (¶ 0124).
Pi (US 2022/0237814 A1) teaches calculating a confidence of an estimated pose (Abstract) wherein the pose prediction apparatus uses sensors to measure user motion for a predetermined period of time and predicts a pose at a future time using confidence and weights (¶ 0017).
Freese (US 2021/0215940 A1) teaches forward prediction parameters, similar to time delay parameters, to account for time delays from the time content is generated to the time the content is presented for display wherein the HMD’s pose and objects’ poses are predicted from motion and time delay information (¶¶ 0048, 0051, and 0071).
Salmani Rahimi (US 11,335,077 B1) teaches sensory dissonance due to render latency in artificial reality environments (col. 14, ll. 4–30) and predicting pose of detected objects using motion or other physics-based predictive models using time periods (col. 15, ll. 42–67).
Garvey (US 2021/0304483 A1) teaches predicting the pose of the HMD and the motion of one or more objects at the predicted time of final rendering (¶ 0063).
Wang (US 2019/0251696 A1) teaches predicting poses according to time points (e.g. ¶ 0138).
Kuwahara (US 2018/0047332 A1) teaches latency compensation for time warping a rendered image to a display (¶ 0071) and using a weighted average of past pose estimations to inform a future pose estimation (¶ 0074).
eVRydayVR, “Oculus Rift - How Does Time Warping Work?,” Youtube, Published on: Apr. 19, 2014, Available at: http://www.youtube.com/watch?v=WvtEXMIQQti.
Levine (US 2022/0350365 A1) teaches consideration of pose estimate accuracy based on pose estimate time stamp (¶ 0021).
Kirchner (US 2023/0221795 A1) teaches pose estimation accuracy and/or integrity evaluated based on time differences between pose updates (¶ 0060).
McMillan et al., “Head-tracked stereoscopic display using image warping,” In S. Fisher, J. Merritt, and B. Bolas, editors, Proceedings SPIE, volume 2409, pages 21–30, San Jose, CA, Feb 1995.
fMark et al., “Post-Rendering 3D Warping,” In Proc. of 1997 Symp. On Interactive 3D Graphics, Providence, RI, Apr. 27–30, 1997, pp. 7–16.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael J Hess whose telephone number is (571)270-7933. The examiner can normally be reached Mon - Fri 9:00am-5:30pm.
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/MICHAEL J HESS/Examiner, Art Unit 2481
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