DETAILED ACTION
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 .
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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Qian et al. “An eye tracking based virtual reality system for use inside magnetic resonance imaging systems. Sci Rep 11, 16301 (2021).” (cited on the IDS and provided by Applicant, hereinafter Qian) in view of Uscinski et al. U.S. Patent Publication No. 2018/0348861 (hereinafter Uscinski).
Consider claim 1, Qian teaches a method of auto-calibrating an eye gaze tracking system for a user (Page 6, adaptive gaze prediction), the method comprising: providing a model linking eye data with a gaze position on a display (Page 6, adaptive gaze prediction), wherein the model links user eye feature locations and user head locations to gaze locations (Figure 3a, pupil tracking (inner words). Page 6, head motion estimation and pupil detection); acquiring user eye data and transforming the acquired user eye data into a local eye image space to obtain an indication of user eye feature location and an indication of user head location in eye image space (Figures 3b-c, progressive calibration based gaze interaction interface; Page 6, Adaptive gaze prediction); providing an icon at a known position on the display, the icon being associated with a collider area (Figure 3c, Interactive visual scene. Page 7, User interface design and landing zone. Page 4, object’s collider (landing zone) and visual shape); transforming the known position to accord with the local eye image space (Page 7, UI interaction is based on selection
by gaze fixation); estimating, based upon the model and the transformed acquired user eye data and the transformed known position, whether a user gaze position falls within the collider area(Page 7, UI interaction is based on selection by gaze fixation; If the gaze remains in the landing zone, the visible menu item will shrink until, after a preset dwell time, selection is confirmed by the menu item vanishing and the resulting action commencing); based on determining the estimated user gaze position falls within the collider area, associating the transformed acquired user eye data with the transformed known position (Page 7, UI interaction is based on selection by gaze fixation;; and adapting the model based upon the transformed known position and associated transformed acquired eye data (Page 6, Adaptive gaze prediction and each time a selection is made, a new piece of calibration data becomes available).
Qian does not appear to mention “centralized” eye image.
However, in a related field of endeavor, Uscinski teaches eye tracking calibration (abstract) and further teaches “centralized” eye image ([0131], centered in the pupil).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to provide a centralized eye image with the benefit that a current eye pose can be measured with reference to an eye pose direction, which is a direction orthogonal to the surface of the eye (and centered in the pupil) but oriented toward the object at which the eye is currently directed as suggested in [0131].
Consider claim 2, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the indication of user eye feature location comprises an indication of user eye pupil location (Figure 3a, pupil tracking).
Consider claim 3, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the indication of user head location comprises an indication of a location of a facial anchor (Figure 3a, eye corner selection and region generation).
Consider claim 4, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the model (Page 6, adaptive gaze prediction, model) comprises a model which maps the local eye image space to a display gaze position which has been transformed into an equivalent transformed gaze space (Page 7, UI interaction is based on selection by gaze fixation).
Consider claim 5, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the local eye image space comprises a coordinate system in which an eye tracking origin coordinate used when acquiring user data from an eye image is transformed and scaled to map to an image center (Page 7, UI interaction is based on selection by gaze fixation. Page 6, each selection target has a landing zone (the region of the VR space associated with it) that is initially large, but gradually reduces over time as the gaze prediction model becomes more robust and accurate).
Consider claim 6, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein transformed known positions comprise display locations which have been transformed to account for origin and scale transformations applied to data from an eye image (Page 7, UI interaction is based on selection by gaze fixation. Page 6, each selection target has a landing zone (the region of the VR space associated with it) that is initially large, but gradually reduces over time as the gaze prediction model becomes more robust and accurate).
Consider claim 7, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the icon comprises a visual target and an associated virtual collider area (Page 7, User interface design and landing zone. Page 4, object’s collider (landing zone) and visual shape).
Consider claim 8, Qian and Uscinski teach all the limitations of claim 1.
Qian does not appear to specifically disclose the associated virtual collider area has a diameter at least twice the diameter of the visual target.
However, Qian teaches in page 4, the interactive targets in our
scene normally have a landing zone larger than the associated visual shape to capture ambient fixation.
Therefore, it would have obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to provide a particular size in order to achieve design choices. It has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art, In re Aller, 105 USPQ 233 (C.C.P.A. 1955).It has been held that discovering an optimum value of a result effective variable involves only routine skill in the art, In re Antonie, 195 USPQ 6 (C.C.P.A. 1977).
Consider claim 9, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the collider area is centred upon the known position (Figure 2, collider and visual object).
Consider claim 10, Qian and Uscinski teach all the limitations of claim 1. In addition, Qian teaches wherein the icon comprises an adaptive icon at the known position on the display, the adaptive icon being configured to adapt when the estimate that the estimated user gaze position falls within the collider area (Page 4, The effector and animator generate visual effects (such as highlight, fade, dissolve, particle effect etc.) and animations (such as motion captured animation, shrinkage etc.) of the visual object when the subject’s gaze
dwells on the object’s collider (landing zone)).
Consider claim 11, Qian and Uscinski teach all the limitations of claim 10. In addition, Qian teaches wherein adapting the icon while the estimated user gaze position is determined to fall within the collider area (Page 4, The effector and animator generate visual effects (such as highlight, fade, dissolve, particle effect etc.) and animations (such as motion captured animation, shrinkage etc.) of the visual object when the subject’s gaze dwells on the object’s collider (landing zone)).
Consider claim 12, Qian and Uscinski teach all the limitations of claim 10. In addition, Qian teaches wherein the method further comprises performing steps comprising: acquiring further user eye data and transforming the further acquired user eye data into the local eye image space to obtain another indication of user eye feature location and another indication of user head location in the eye image space (Page 6, Each time
a selection is made, a new piece of calibration data becomes available; to achieve robustness, each selection target has a landing zone (the region of the VR space associated with it); account for head motion); providing an additional icon at a further known position on the display, the additional icon being associated with an additional collider area and transforming the further known position to accord with the local eye image space (Page 6, Each time
a selection is made, a new piece of calibration data becomes available; to achieve robustness, each selection target has a landing zone (the region of the VR space associated with it); estimating, based upon the model and transformed further acquired user eye data, and the transformed further known position whether an additional user gaze position falls within the additional collider area (Page 7, UI interaction is based on selection by gaze fixation; If the gaze remains in the landing zone, the visible menu item will shrink until, after a preset dwell time, selection is confirmed by the menu item vanishing and the resulting action commencing); based on determining the additional estimated user gaze position falls within the additional collider area (Page 7, UI interaction is based on selection by gaze fixation), associating the further transformed acquired further user eye data with the transformed further known position (Page 6, Adaptive gaze prediction and each time a selection is made, a new piece of calibration data becomes available); and further adapting the model based upon the transformed further known position and associated transformed further acquired eye data (Page 6, Adaptive gaze prediction and each time a selection is made, a new piece of calibration data becomes available). In addition, Uscinski teaches “centralized” eye image ([0131], centered in the pupil), see motivation to combine in claim 1.
Consider claim 13, Qian and Uscinski teach all the limitations of claim 12. In addition, Qian teaches wherein the method comprises iterating the model linking eye data with gaze positions on the display to auto-calibrate for a user (Page 6, each selection target has a landing zone (the region of the VR space associated with it) that is initially large, but gradually reduces over time as the gaze prediction model becomes more robust and accurate).
Consider claim 14, Qian and Uscinski teach all the limitations of claim 13. In addition, Qian teaches changing a size of the collider area as part of a series of iterative steps to refine the auto-calibration of the eye gaze tracking system for the user (Page 6, each selection target has a landing zone (the region of the VR space associated with it) that is initially large, but gradually reduces over time as the gaze prediction model becomes more robust and accurate).
Consider claim 15, Qian and Uscinski teach all the limitations of claim 13. In addition, Qian teaches wherein changing the size of the collider area comprises: reducing a relative size of the collider area compared to the icon (Page 6, each selection target has a landing zone (the region of the VR space associated with it) that is initially large, but gradually reduces over time as the gaze prediction model becomes more robust and accurate).
Consider claim 16, Qian and Uscinski teach all the limitations of claim 13. In addition, Qian teaches wherein the known position comprises a position substantially in a centre of the display (Figure 3c, “Go”. Figure 6, calibration point located in the center of the display).
Consider claim 17, Qian and Uscinski teach all the limitations of claim 13. In addition, Qian teaches wherein the known position comprises a position at a periphery of the display (Figure 3c, “Game”. Figure 6, calibration points located at the periphery of the display).
Consider claim 19, it includes limitations mentioned in claim 1, and thus these limitations are rejected by the same reasoning. In addition, Qian teaches at least one processor; and at least one memory storing instructions that, when executed by the at least one processor (Figure 1a-c, computer and eye and table tracking modules).
Conclusion
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/ROBERTO W FLORES/Primary Examiner, Art Unit 2621
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