DETAILED ACTION
In Applicant’s Response dated 4/5/2026, Applicant amended claims 1 to 20; and argued against all rejections previously set forth in the Office action dated 1/6/2026.
In view of Applicant’s amendments and remarks, the 35 USC 101 and 112 rejections are withdrawn.
Response to Argument
Applicant’s arguments were considered, but are moot in view of the new ground(s) of rejection.
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.
Claim(s) Claim(s) 1, 2, 3, 4, 7, 9, 10, 11, 12, 13, 17, 18, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Prada, Patent No.: 8558759B1, in view of Browy, Pub. No.: US 20180075659 A1.
With regard to claim 1:
Prada discloses the aspect Eyewear, comprising: a frame configured to be worn on a head of a user (see fig. 1 for the eyewear paragraph 40 column 7 line 44 to line 50: “FIG. 1a illustrates an example wearable computing system 100 for receiving, transmitting, and displaying data. In accordance with an example embodiment, the wearable computing system 100 is depicted as a wearable HMD taking the form of eyeglasses 102. However, it will be appreciated that other types of wearable computing devices could additionally or alternatively be used.”); a camera supported by the frame and configured to capture an image in front of the camera including a hand gesture ( the HMD 502 can recognize that a hand gesture is being or has been made by using a video camera (such as video camera 120 in FIG. 1, for example), see fig. 1a for camera 120 on the eyewear, paragraphs 93: “In further accordance with the example embodiment, the HMD 502 can recognize that a hand gesture is being or has been made by using a video camera (such as video camera 120 in FIG. 1, for example) to monitor the FOV for one or more triggering events or criteria. For example, the video camera could monitor the FOV for a particular marker, such as a ring bearing a known pattern, which could then be used to signal the presence of a user's hand within a spatial region designated for hand gestures (among other purposes). As another example, the video camera could monitor the FOV for the appearance of an object or item having a color or tone that matches or resembles one or more cataloged colors and/or tones considered to be representative of a variety of skin colors. Again, this could indicate the presence of a user's hand within a spatial region designated for hand gestures. It will be appreciated that other criteria or events could signal the presence of a user's hand, and trigger hand gesture analysis.”); and a processor configured to: receive the image including the hand gesture from the camera ( the HMD 502 can recognize that a hand gesture is being or has been made by using a video camera (such as video camera 120 in FIG. 1, for example), see fig. 1a for camera 120 on the eyewear, paragraphs 93: “In further accordance with the example embodiment, the HMD 502 can recognize that a hand gesture is being or has been made by using a video camera (such as video camera 120 in FIG. 1, for example) to monitor the FOV for one or more triggering events or criteria. For example, the video camera could monitor the FOV for a particular marker, such as a ring bearing a known pattern, which could then be used to signal the presence of a user's hand within a spatial region designated for hand gestures (among other purposes). As another example, the video camera could monitor the FOV for the appearance of an object or item having a color or tone that matches or resembles one or more cataloged colors and/or tones considered to be representative of a variety of skin colors. Again, this could indicate the presence of a user's hand within a spatial region designated for hand gestures. It will be appreciated that other criteria or events could signal the presence of a user's hand, and trigger hand gesture analysis.”); and generate a command that is indicative of the identified hand gesture, wherein the command is configured to initiate the camera to take an image (the FOV shows content captured by the camera, paragraph 27 and 28 column 5 line 33 to line 47: “In an example embodiment, a HMD can be further equipped with a video camera device capable of capturing video and still-image data of a FOV of the HMD. For example, the video camera device can have a FOV that is the same as, or substantially overlapping that of, a user or wearer of the HMD. Video and still-image data captured by the video camera device can serve as a form of input to the HMD.” ) of an object in front of the camera (see fig 9 wherein the user can take a image based on the L shaped gesture paragraphs 123 to 125 column 22 line to line 42 to line 63: “FIGS. 9a and 9b illustrate how the apparent size of a symbolic right angle the FOV of a HMD can be used to define or demark a portion of the FOV for image selection. Each of FIGS. 9a and 9b depict a city skyline being viewed within a FOV 902. In FIG. 9a, a hand 903-1 is shown as making a right-angle gesture within the FOV 902. This view corresponds to the example illustrated in FIG. 8a, so that the hand 903-1 appears relatively small in the FOV 902. Accordingly, a symbolic right angle appears to subtend a relatively small bounding box 904-1 in the FOV 902. The bounding box 904-1 correspondingly encloses a relatively small portion of the example skyline viewed in the FOV 902. Upon determining that a right-angle-shaped hand gesture has been made, the HMD generates an image of the FOV within the bounding box 904-1. The generated image 906 is represented to the right side of FIG. 9a, with a zigzagging arrow indicating its having originated from the right-angle-shaped hand gesture in the FOV 902. Once the image is generated, the HMD could be transmitted it to a social networking service in a message that includes an indication an identity of a subscriber and a request to post the image, as described above.”).
Prada does not disclose the aspect of identify the hand gesture of the user as-presenting sign language directly in front of the camera.
However Browy discloses the aspect of identify the hand gesture of the user as-presenting sign language directly in front of the camera (Browy the wearable system 200 can interpret sign language by, for example, detecting gestures that may constitute sign language, paragraph 139: “The wearable system 200 can implement a sensory eyewear system 970 for facilitating user's interactions with the other people or with the environment. As one example of interacting with other people, the wearable system 200 can interpret sign language by, for example, detecting gestures that may constitute sign language, translating the sign language to another language (e.g., another sign language or a spoken language), and presenting the translated information to a user of a wearable device. As another example, the sensory eyewear system 970 can translate speech into sign language and present the sign language to the user”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Browy to Prada so the system can also interpret sign language from the user can able to use to issue commands or perform functions based on the sign language.
With regard to claims 2 and 11:
Prada and Brawy disclose the aspect of the eyewear of claim 1, wherein the processor is configured to use a convolutional neural network (CNN) to identify the hand gesture (Browy paragraph 152: “The wearable system 200 can convert the captured sign language to text which can be presented to a user or translated into another language. Conversion of sign language to text can be performed using algorithms such as deep learning (which may utilize a deep neural network), hidden Markov model, dynamic programming matching, etc. For example, the deep learning method (a convolutional neural network in some cases) can be trained on images or videos containing known signs (supervised learning) so as to determine features representative of the signs and to build a classification model based on the learned features. Such a trained deep learning method can then be applied by the local processing and data module 260 or the remote processing module and data repository 270, 280 of the wearable system 200 to images of a signer detected by the outward-facing imaging subsystem.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Browy to Prada so the system can use CNN to interpret hand gesture in order to improve accuracy and allow training and improvements.
With regard to claims 3 and 12:
Prada and Brawy disclose the aspect of the eyewear of claim 1, wherein the processor is configured to identify the hand gesture by matching the hand gesture in the image to a set of hand gestures (Prada paragraph 92 column 16 line 44 to line 60: “In accordance with an example embodiment, the HMD can recognize that a hand gesture is being or has been made, and may then identify or match the recognized hand gesture against a library (or other list or collection) of known hand gestures in order to determine one or more actions to take or invoke in response to the gesture. Thus, a user, such as the example user 501, can interact (e.g., provide input data and/or commands) with a HMD, such as the HMD 502, by performing or making a hand gesture in region of space viewable by the HMD. In practice, the viewable region of space for hand gestures of a user of a HMD can be a forward FOV of the HMD, within about an arm's length from the front (forward-facing side) of the HMD. The characterization of "an arm's length" in front of a HMD provides a useful example of a hand gesture space or region, but is not intended to limit the possible region of space around a wearable HMD in which hand gestures for interaction with the HMD could be used.”).
With regard to claims 4 and 13 and 19:
Prada and Brawy disclose the aspect of the eyewear of claim 1, wherein the command is configured to initiate a predefined function (Prada paragraph 92 column 16 line 44 to line 60: “In accordance with an example embodiment, the HMD can recognize that a hand gesture is being or has been made, and may then identify or match the recognized hand gesture against a library (or other list or collection) of known hand gestures in order to determine one or more actions to take or invoke in response to the gesture. Thus, a user, such as the example user 501, can interact (e.g., provide input data and/or commands) with a HMD, such as the HMD 502, by performing or making a hand gesture in region of space viewable by the HMD. In practice, the viewable region of space for hand gestures of a user of a HMD can be a forward FOV of the HMD, within about an arm's length from the front (forward-facing side) of the HMD. The characterization of "an arm's length" in front of a HMD provides a useful example of a hand gesture space or region, but is not intended to limit the possible region of space around a wearable HMD in which hand gestures for interaction with the HMD could be used.”).
With regard to claim 7:
Prada and Brawy disclose the aspect of the eyewear of claim 1, wherein the processor is configured to identify a word from a series of hand gestures (Browy paragraph 177: “FIG. 13A shows an example user experience of a sensory eyewear system where the sensory eyewear system can interpret a sign language (e.g., gestured by a signer) for a user of a wearable system. This example shows a signer 1301 who the user of a sensory eyewear system is observing. The user can perceive that the signer 1301 is making a sequence 1300 of hand gestures as shown in the scenes 1305, 1310, and 1315. The hand gesture in the scene 1305 represents the word “how”; the hand gesture in the scene represents the word “are”; and the hand gesture in the scene 1315 represents the word “you”. Thus the sequence 1300 can be interpreted as “How are you”. The sequences 1320 and 1340 show the same gestures as the sequence 1300. The gesture 1305 corresponds to the gestures 1325 and 1345; the gesture 1310 corresponds to the gestures 1330 and 1350; and the gesture 1315 corresponds to the gestures 1335 and 1355. However, the sequences 1300, 1320, and 1340 illustrate different user display experience as further described below.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Browy to Prada so the system can also interpret sign language from the user can able to use to issue commands or perform functions based on the sign language.
With regard to claims 9 and 17:
Prada and Brawy disclose the aspect of the eyewear of claim 1, wherein the hand gesture comprises a moving hand gesture (Prada, paragraph 127 column 23 line 15 to line 21: “The sizes of the images 906 and 908 differ by virtue of the different apparent sizes of the symbolic right angles formed by the hands 904-1 and 904-2 in FIGS. 9a and 9b. In accordance with the example embodiment, then, the size of an image selected using a right-angle-shaped hand gesture could be adjusted by moving the hand back and forth along the line of sight.”).
Claim 10 is rejected for the same reason as claim 1.
Claim 18 is rejected for the same reason as claim 1.
Claim(s) 5 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Prada, in view of Browy, and further in view of Osborn, Pub. No.: 2023/0072423A1.
With regard to claims 5 and 14:
Prada and Brawy do not disclose the aspect wherein the predefined function is setting a timer.
However Osborn discloses the aspect wherein the predefined function is setting a timer using gesture. (paragraph 1653: “As the user rolls their wrist clockwise, for example, the duration of the timer may increase, and the smart or virtual assistant may provide auditory feedback to the user (i.e. ‘1 minute’, ‘2 minutes’, ‘3 minutes’, etc.). If the user accidentally selects a timer duration greater than intended, the user may roll their wrist counterclockwise while receiving further auditory feedback from the smart or virtual assistant, so that the user may select an intended timer duration. Once the correct duration has been selected, another “pinch tap” gesture may set the timer and the smart or virtual assistant will notify the user after the appropriate amount of time. At any point in this process, a “flick” gesture may enable a user to exit the timer setting module.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Osborn to Prada and Brawy so the user would be able to use the eyewear’s camera to capture his or her gesture in order to perform the function of setting a timer, saving time and effort.
Claim 6 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Prada, in view of Browy, and further in view of Shiplacoff, Pub. No.; 20130346921 A1
With regard to claim 6 and 15:
Prada and Brawy do not disclose the eyewear of claim 4, wherein the processor is configured to launch a third-party application responsive to the identified hand gesture.
However Shiplacoff discloses the aspect wherein the processor is configured to launch a third-party application responsive to the identified hand gesture. (paragraph 143: “The foregoing examples have been described in the context of transitioning a computing device from a limited access state to a different access state. However, the concept and implementation of a light field of objects generated at a touch-sensitive display of a computing device and with which a user can interact via the display can be employed in any of a number of different contexts of using a computing device. For example, after a computing device has been transitioned to an unlocked state, a light field can be employed in a variety of geometric configurations, e.g. concentric circles or a rectangular grid, to invoke one or more functions of the operating system of or a particular application executed by the computing device. For example, the computing device can cause the touch-sensitive display to generate a partially or completely transparent grid of dots on a portion of the display when in an unlocked state. In one such an example, when a user activates, e.g., a particular location on the display and then swipes across a portion or all of the grid of dots, the computing device can cause the display to increase the opacity of dots in the grid based on the proximity of the dots to the user gesture, e.g., in the manner described above with reference to FIGS. 2 and 8A-8C. Additionally, upon completion of the gesture, the computing device can invoke one or more functions, e.g. launch an operating system or third-party application on the computing device.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Shiplacoff to Prada and Brawy so the user would be able to use the gesture to quick access third party applications saving time and efforts.
Claims 8 and 16 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Prada, in view of Browy, and further in view of Itzhaik, Pub. No.: US 20150084859 A1.
With regard to claim 8:
Prada and Brawy do not disclose discloses the eyewear of claim 7, wherein the processor is further configured to auto-complete spelling of the word.
However Itzhaik wherein the processor is further configured to auto-complete spelling of the word after identifying a word using hand gesture (paragraph 59: “FIG. 4 is a flowchart schematically illustrating a process and method for cross-matching of multiple inputs each input is a gesture of different body parts mainly hand movement and lips movement for lingual signs identification and verification, according to some embodiments of the present invention. In this process the processor receives data indicative of simultaneous inputs from the multiple sensing and/or input devices 31 such as hands and lips movements gestures, where the hand movement gestures are in sign language and performed by the user simultaneously while speaking the words using lips movements in front of at least one camera positioned to capture both the hands movements as well as the lips movements of the user. The received data is then processed and analyzed using gesture recognition algorithms one adapted to decode hand movements gestures and the other to decode lips movements gestures 33-34. The decoding of the hands movements gesture results in identifying a first lingual sign (i.e. a phoneme, a syllable, a symbol, a word etc.) associated with the first input and the decoding of the simultaneous lips movements gesture results in identifying a second lingual sign associated with the second input. The first lingual sign may then be compared to the second lingual sign 35 for verification thereof, following the method described in relation to FIG. 3 for cross-matching the identified signs and optionally for auto-completion of text.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Itzhaik to Prada and Brawy so the user would be able to have their gestured words autocompleted saving time and effort without having to complete the words themselves.
With regard to claims 16 and 20:
Prada and Brawy disclose identifying a word from a series of hand gestures (Browy paragraph 177: “FIG. 13A shows an example user experience of a sensory eyewear system where the sensory eyewear system can interpret a sign language (e.g., gestured by a signer) for a user of a wearable system. This example shows a signer 1301 who the user of a sensory eyewear system is observing. The user can perceive that the signer 1301 is making a sequence 1300 of hand gestures as shown in the scenes 1305, 1310, and 1315. The hand gesture in the scene 1305 represents the word “how”; the hand gesture in the scene represents the word “are”; and the hand gesture in the scene 1315 represents the word “you”. Thus the sequence 1300 can be interpreted as “How are you”. The sequences 1320 and 1340 show the same gestures as the sequence 1300. The gesture 1305 corresponds to the gestures 1325 and 1345; the gesture 1310 corresponds to the gestures 1330 and 1350; and the gesture 1315 corresponds to the gestures 1335 and 1355. However, the sequences 1300, 1320, and 1340 illustrate different user display experience as further described below.”).
Prada and Brawy do not disclose the aspect wherein the processor auto-completes spelling of the word.
However Itzhaik discloses the aspect of identifying a word from a series of hand gestures, wherein the processor auto-completes spelling of the word (paragraph 59: “FIG. 4 is a flowchart schematically illustrating a process and method for cross-matching of multiple inputs each input is a gesture of different body parts mainly hand movement and lips movement for lingual signs identification and verification, according to some embodiments of the present invention. In this process the processor receives data indicative of simultaneous inputs from the multiple sensing and/or input devices 31 such as hands and lips movements gestures, where the hand movement gestures are in sign language and performed by the user simultaneously while speaking the words using lips movements in front of at least one camera positioned to capture both the hands movements as well as the lips movements of the user. The received data is then processed and analyzed using gesture recognition algorithms one adapted to decode hand movements gestures and the other to decode lips movements gestures 33-34. The decoding of the hands movements gesture results in identifying a first lingual sign (i.e. a phoneme, a syllable, a symbol, a word etc.) associated with the first input and the decoding of the simultaneous lips movements gesture results in identifying a second lingual sign associated with the second input. The first lingual sign may then be compared to the second lingual sign 35 for verification thereof, following the method described in relation to FIG. 3 for cross-matching the identified signs and optionally for auto-completion of text.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Itzhaik to Prada and Brawy so the user would be able to have their gestured words autocompleted saving time and effort without having to complete the words themselves.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
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/DI XIAO/Primary Examiner, Art Unit 2178
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