Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAIL ACTION
Notice to Applicant(s)
This application has been examined. Claims 1-20 are pending.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bao et al. (2018/0088323).
As per claim 1, Bao et al. disclose a method for compensating latency in an automotive augmented reality head-up display (AR-HUD) (see at least figure 1C) which includes the steps of receiving object positional data from a vehicle sensor system (see at least figure 1C, item 116); capturing real-time image data from a vehicle-mounted camera (see at least figure 1C, item 106); deriving real-world features from the image data using an image analysis algorithm and/or tracking with appearance (see at least figure 1C, item 112); and correcting a displayed virtual object by snapping the virtual object highlight to a nearest feature boundary when a threshold proximity is met (see at least figure 1C, item 118).
As per claim 2, Bao et al. disclose that the vehicle sensor system comprises a camera (see at least figure 2A, item 216).
As per claim 3, Bao et al. disclose that the camera is a monocular located forward-facing in the vehicle cabin (see at least figure 13).
As per claim 4, Bao et al. disclose that the image processing method in at least figure 2A, 14 and paragraphs 0049, 0124.
As per claim 5, Bao et al. disclose that the image analysis algorithm comprises a neural network-based model selected from object detection (see at least paragraphs 0109, 0161).
As per claim 6, Bao et al. disclose that the limitation of this claim in at least figure 16 and paragraph 0140.
As per claim 7, Bao et al. disclose the applying predictive modeling to forecast object trajectories and pre-render virtual overlays (see at least paragraphs 0119, 0120, 0161).
As per claim 8, Bao et al. disclose the step of rendering adaptive overlays based on context hazard alerts (see at least paragraphs 0040, 0053).
As per claim 9, Bao et al. disclose the step of transmitting sensor and camera data over automotive Ethernet (see at least paragraphs 0066, 0072).
As per claim 10, Bao et al. disclose the step of updating virtual overlays after each HUD display refresh cycle (see at least paragraph 0078).
With respect to claims 11 and 18, the limitations of these claims have been noted in the rejections above. They are therefore considered rejected as set forth above.
As per claim 12, Bao et al. disclose the execute sensor fusion algorithms that combine high-accuracy and fast-response sensor outputs (see at least figure 8).
As per claim 13, Bao et al. disclose that the display comprises a windshield-integrated head-up display with high-refresh rates and adaptive brightness control (see at least figure 1C; paragraph 0038).
As per claim 14, Bao et al. disclose that the object snapping is applied only when a positional difference between virtual highlight and a detected feature boundry exceeds a predetermined latency threshold (see at least figure 16; paragraph 0140).
As per claim 15, Bao et al. inherently disclose that the dynamic objects including pedestrians are prioritized for latency correction over static objects including road signs or markers (see at least figure 1C, paragraph 0120).
As per claim 16, Bao et al. disclose a memory configured to store historical
sensor data to enable predictive trajectory modeling (see at least paragraphs 0132, 0160).
As per claim 17, Bao et al. disclose that the sensor fusion further comprises correlation logic configured to validate object identification across disparate sensors (see at least paragraphs 0049, 0093, 0095).
As per claim 19, Bao et al. disclose that the real-time adjustments include recoloring of overlays based on contextual priority of detected objects (see at least figure 4B; paragraphs 0063, 0078, 0080, 0114, 0115).
As per claim 20, Bao et al. disclose that the AR processor prioritizes computational resources for overlays rendered in the forward-view region visible to the driver (see at least paragraphs 0049, 0114, 0115, 0120).
Conclusion
All claims are rejected.
The following references are cited as being of general interest: Seder et al. (2010/0289632), Holz et al. (2016/0048725), Kim (2016/0163108), Huang et al. (2021/0349459), Sucan et al. (2022/0066440) and Bork et al. (2026/0116186).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAN QUANG NGUYEN whose telephone number is (571) 272-6966. The examiner can normally be reached on Monday to Thursday from 7:00am to 5:30pm.
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September 25, 2026
/TAN Q NGUYEN/Primary Examiner, Art Unit 3661
