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 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Marvit et al. (US 2005/0212911, hereinafter "Marvit") in view of Ali et al. (US 2023/0333660, hereinafter "Ali").
With respect to Claim 1 (Original), Marvit teaches a method comprising:
detecting, using a [sensor] system associated with a computing device, a gesture performed by a user, the gesture associated with a [sensor]-signal characteristic (Marvit: Para. [0004], [0038], motion detection module operable to detect motion of the handheld device within three dimensions);
comparing the [sensor]-signal characteristic associated with the gesture performed by the user to one or more stored [sensor]-signal characteristics, the comparing effective to determine a lack of correlation to one or more known gestures with which the one or more stored [sensor]-signal characteristics are associated, the one or more known gestures associated with one or more known commands (Marvit: Para. [0147], device may query the user to determine if the user desires to store an unrecognized gesture, indicating a lack of correlation to known gestures in the gesture database);
receiving, proximate with detecting the gesture, a new command (Marvit: Para. [0147]-[0148], function mapping information for the gesture is received from the user);
responsive to the comparing effective to determine the lack of correlation and the receiving the new command, determining that the gesture is a new gesture associated with the new command (Marvit: Para. [0147]-[0148], mapping the unrecognized gesture to the received function mapping information to be commanded); and
storing the associated [sensor]-signal characteristic to enable recognition of the new gesture at a future time effective to cause performance of the new command (Marvit: Para. [0147]-[0148], storing the gesture and function mapping information in a gesture mapping database so the user may utilize the gesture as motion input in the future).
Marvit fails to expressly disclose:
detecting, using a radar system associated with a computing device, and wherein the signal characteristic is a radar-signal characteristic.
However, Ali discloses:
detecting, using a radar system associated with a computing device (Ali: Para. [0006], [0086], triggering a device to obtain radar data using a mmWave FMCW transceiver), and
wherein the signal characteristic is a radar-signal characteristic (Ali: Para. [0103], [0138], detecting a gesture based on time-velocity data (TVD) radar-signal characteristics extracted from the reflected signal).
Therefore, it would be obvious to one of ordinary skill in the art to modify the method, as taught by Marvit, to incorporate a radar system and radar-signal characteristics, as taught by Ali, in order to overcome the limitations of optic and accelerometer sensors such as sensitivity to ambient lighting conditions and privacy concerns (Ali: Para. [0004]).
With respect to Claim 2, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein the detecting the gesture is performed at the computing device associated with the radar system and wherein the receiving the new command is performed by the computing device (Marvit: Para. [0035] - [0038], handheld computing device 10 receives input 14 and processes motion locally).
With respect to Claim 3, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein the comparing effective to determine the lack of correlation to the one or more known gestures with which the one or more stored radar-signal characteristics are associated determines the lack of correlation based on failing to meet confidence threshold criteria (Marvit: Para. [0149]-[0154], utilizing precision levels and allowable differences to determine if a gesture constitutes a recognized match; Ali: Para. [0201], [0238]-[0239], using a SoftMax activation function to output probabilities indicating the likelihood that the user performed the corresponding gesture).
With respect to Claim 4, the combination of Marvit as modified by Ali teaches the method of claim 3, wherein the confidence threshold criteria is associated with a low confidence, and wherein the comparing is at or below the confidence threshold criteria for each of the one or more stored radar-signal characteristics (Marvit: Para. [0104], [0153], comparing the matrix of the movement with the matrices of each recognizable gesture and failing to assign it to any particular gesture known to the device, indicating the correlation is at or below the required threshold for every stored gesture characteristic; Ali, Para. [0239], failing to achieve high probability score across the SoftMax outputs fundamentally represents a low confidence in the match).
With respect to Claim 5, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein detecting the gesture associated with the radar-signal characteristic further comprises determining the radar-signal characteristic (Ali: Para. [0134]-[0138], converting raw radar signals to generate a TVD column from a radar frame).
With respect to Claim 6, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein receiving the new command is performed prior to detecting the gesture performed by the user (Marvit: Para. [0147], disclosing that the indication for gesture creation may be received before the user moves the device).
With respect to Claim 7, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein receiving, proximate with detecting the gesture, the new command receives the new command and detects the gesture within five seconds of each other. Establishing a five-second timeout window for sequential interface inputs is a well-known design choice in the art to ensure inputs are sufficiently proximate, thus reliably associating the gesture with the command without excessive delay.
With respect to Claim 8, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein receiving, proximate with detecting the gesture, the new command receives the new command and detects the gesture without an intervening gesture attempt or other command initiated by the user (Marvit: Para. [0147], the device queries the user immediately upon detecting an unrecognized gesture, receiving the command directly without intervening inputs).
With respect to Claim 9, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein detecting the gesture comprises determining that the radar-signal characteristic of the gesture is associated with an intentional motion performed by the user, the intentional motion not corresponding to a background motion (Ali: Para. [0122]-[0123], gating mechanism determines whether activity in a radar signal corresponds to non-gesture activities or intentional gesture-related activities, filtering out background movement).
With respect to Claim 10, the combination of Marvit as modified by Ali teaches the method of claim 1, the method further comprising:
detecting, using the radar system and at the computing device, a second radar-signal characteristic associated with a presence of the user (Ali: Para. [0053], using the radar to perform proximity sensing, liveness detection, and vital sign monitoring), the second radar-signal characteristic usable to determine that the user is a registered user; and responsive to determining the user is the registered user, correlating the new gesture to the registered user (Marvit: Para. [0111]-[0112], utilizing a “spatial signature” tracked by motion detectors to “serve as an effective form of authentication”; Para. [0143]-[0144], [0161], determining the user using the device based on “the manner in which the user moves the device for motion input” and accessing “user identities 381” to perform user-specific gesture mappings. Detecting a distinct spatial signature motion for authentication prior to detecting the new custom gesture requires identifying a separate and chronologically unique second signal characteristic.).
Therefore, it would be obvious to one of ordinary skill in the art to modify the spatial signature authentication method, as taught by Marvit, to incorporate the radar proximity and motion sensing capabilities, as taught by Ali, in order to capture the user’s authentication motion as a second radar signal characteristic that confirms physical presence and authenticates their registered identity (Marvit: Para. [0143]-[0144]).
With respect to Claim 11, the combination of Marvit as modified by Ali teaches the method of claim 10, wherein the new gesture is correlated with the registered user and not a different user (Marvit: Para. [0144], isolating functions to a specific user such that “if User 1 is using the device, then the device performs Function 1 at step 320a; if User 2 is using the device, then the device performs Function 2”), the method further comprising: recognizing, at the future time, performance of the new gesture based at least in part on detecting the presence of the registered user using the second radar-signal characteristic (Marvit: Para. [0143]-[0144], recalling specific gesture mapping assigned to that unique user upon detecting their spatial signature and authenticating their identity).
With respect to Claim 12, the combination of Marvit as modified by Ali teaches the method of claim 11, wherein the new command is associated with two or more gestures, the two or more gestures including: the new gesture when performed by the registered user; and a different gesture when performed by the different user (Marvit: Para. [0146]-[0144], allowing different users of the same device to create distinct motions allowing for” personal significance” and mapping those different user-created gestures to the same underlying function).
With respect to Claim 13, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein the computing device associated with the radar system utilizes a machine-learned model to improve the recognition of the new gesture, the machine-learned model associated with one or more convolutional neural networks (Ali: Para. [0127], [0236]-[0238], gesture classifier processes TVD using a Convolutional Neural Network (CNN) architecture).
With respect to Claim 14, the combination of Marvit as modified by Ali teaches the method of claim 1, wherein the new command is not associated with, or same as, the one or more known commands (Marvit: Para. [0148], the function mapping information may comprise a user-created macro or a long string of characters not previously known to the device).
With respect to Claim 15, the apparatus claimed is equivalent to the method claimed in Claim 1. Therefore, Claim 15 is rendered obvious by the combination of Marvit as modified by Ali as applied to Claim 1.
With respect to Claim 16, the computing device of claim 15 is rendered obvious by the combination of Marvit as modified by Ali as applied to Claim 2.
With respect to Claim 18, the combination of Marvit as modified by Ali teaches the computing device of claim 15, wherein: detecting the gesture associated with the radar-signal characteristic further comprises transmitting the radar-transmit signal, receiving the radar-receive signal, and determining the radar-signal characteristic based on the radar-receive signal (Ali: Para. [0086]-[0087], transmitter transmits a signal and receiver receives the reflected echo to determine object range and velocity); receiving the new command is performed prior to detecting the gesture performed by the user (Marvit: Para. [0147]); and receiving, proximate with detecting the gesture, the new command receives the new command and detects the gesture within five seconds of each other (Obvious design choice as established for Claim 7).
With respect to Claim 19, the computing device of claim 15 is rendered obvious by the combination of Marvit and Ali as applied to Claim 10.
With respect to Claim 20, the computing device of claim 15 is rendered obvious by the combination of Marvit and Ali as applied to Claim 13.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Sheng et al. (see NPL listed on PTO-892) –proposes RadarAE, a novel self-supervised representation learning framework for millimeter-wave radar-based gesture recognition, designed to work effectively with few labeled samples and avoid overfitting.
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/BRYAN EARLES/Primary Examiner, Art Unit 2625
