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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5-8, 22-25 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 5 recites “between first average values” and “differences of second average values”. However, a “first average value” and “second average value” have been previously introduced. This antecedent basis ambiguity renders the scope of the claim indefinite. Similarly, for claim 22.
Dependent claims incorporate all of the limitations of their respective independent or intervening claim(s) and are rejected on the same basis.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8 and 17-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recite(s):
A gesture recognition method, comprising: acquiring an image sequence comprising a human hand, and taking a first image in the image sequence as a target image; determining at least two lines corresponding to fingers in the target image; determining valid lines from the at least two lines; under a condition that a first number of the valid lines is greater than a first number threshold and first angles each between a corresponding one of all of the valid lines and a first coordinate axis of the target image are less than a first angle threshold, determining a subsequent image of the target image as the target image, and returning to the step of determining at least two lines corresponding to the fingers in the target image until the first number is not greater than the first number threshold or one or more of the first angles are not less than the first angle threshold; determining, according to coordinate values of key points on the valid lines in the first image and a second image, a relative moving distance of the human hand in a direction of the first coordinate axis, wherein the second image is a previous image of the target image; recognizing, according to the relative moving distance, a gesture corresponding to changing from the first image to the second image.
The limitations above as drafted, are a process that, under its broadest reasonable interpretation, covers mathematical concepts and mental processes. Specifically, comparison of calculated angles or numbers of fingers against thresholds and determination of moving distance according to coordinate values correspond to mathematical relationships and calculations. Determining valid lines and recognizing a gesture correspond to processes that can be performed in the mind. That is, other than reciting “acquiring an image sequence comprising a human hand, and taking a first image in the image sequence as a target image”, nothing in the claim element precludes the interpretation that the claim corresponds to mathematical concepts and mental processes. If the claim limitation, under its broadest reasonable interpretation, covers mathematical relationships and calculations and mental processes, it falls under the “Mathematical Concepts” and “Mental Processes” groupings of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim recites the additional elements “acquiring an image sequence comprising a human hand, and taking a first image in the image sequence as a target image”. The image of sequence of the human hand appears not to be any further integrated than to perform the abstract ideas of mathematical calculations and gesture recognition on the sequence of images. Thus, the image sequence does not appear to integrate the abstract idea into a practical application. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Acquiring a sequence of images of a human hand is a well-known and performing operations on target images within the sequence is a generic computer technique, and is shown, for example, in Zhao et al. (US Patent Application publication 2020/0393911), Chung et al. (US Patent Application Publication 2021/0081104), and Ahn et al. (US Patent Application Publication 2016/0274667). As discussed above, the steps do not appear to impose any meaningful limits on practicing the abstract idea, and amount to mere instructions to apply the exception using well known computer techniques. The claim is not patent eligible.
Claims 2-6 recite additional mathematical concepts such as calculation of angles, calculating differences, calculating averages, and calculating quotients. These claims do not appear to introduce additional elements beyond the abstract ideas. Similarly for claims 19-23.
Claims 7 and 8 recite additional mathematical concepts such as coordinate axes, comparison of values against a threshold, and additional mental processes such as recognizing a right/left/up/down-dial gesture. These claims do not appear to introduce additional elements beyond the abstract ideas. Similarly for claims 24-25.
Claims 17-18 recites the computer implementation of an application, which also appears to generally link the abstract idea to a particular technological environment. Specifically “an electronic device comprising: a processor; a memory; and programs or instructions stored on the memory and executable by the processor, wherein the programs or instructions, when executed by the processor, implement operations” and “a readable storage medium having programs or instructions stored thereon, wherein the programs or instructions, when executed by a processor, implement steps” respectively. These limitations appear to merely employ a computer as a tool for implementing the abstract ideas. Computer components are well-known in the art, and are shown in, for example, Zhao et al. (US Patent Application publication 2020/0393911), Chung et al. (US Patent Application Publication 2021/0081104), and Ahn et al. (US Patent Application Publication 2016/0274667). Claims 16-17 are not patent eligible.
Claim 18 recites is directed to “a readable storage medium having programs or instructions stored thereon”. Applicant’s Specification appears to recite non-limiting examples of a readable storage medium at ¶00154. As a result, the term “readable storage medium” is interpreted to encompass signals and transmission media, which is non-statutory. Applicant is encouraged to amend the claims to recite a “non-transitory computer readable storage medium” to clearly direct the claim to statutory subject matter.
Prior Art
Listed herein below are the prior art references relied upon in this Office Action:
Zhao et al. (US Patent Application Publication 2020/0393911), referred to as Zhao herein.
Chung et al. (US Patent Application Publication 2021/0081104), referred to as Chung herein.
Ahn et al. (US Patent Application Publication 2016/0274667), referred to as Ahn herein.
Yang et al. (US Patent Application Publication 2013/0106745), referred to as Yang herein.
Peng et al. (US Patent Application Publication 2023/0057965), referred to as Peng herein.
Examiner’s Note
Strikethrough notation in the pending claims has been added by the Examiner.
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) 1-2 and 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Chung.
Regarding claim 1, Zhao discloses a gesture recognition method, comprising (Zhao, Abstract):
acquiring an image sequence comprising a human hand, and taking a first image in the image sequence as a target image (Zhao, Fig. 1 with Abstract and ¶0103 - images of a user’s hand performing a gesture);
determining at least two lines corresponding to fingers in the target image (Zhao, Abstract – vectors representing finger angles);
determining valid lines from the at least two lines (Zhao, Abstract with ¶0137-¶0140 – thresholds are used for determining whether angular changes corresponding to fingers represent valid or invalid gesture inputs);
under a condition that a first number of the valid lines is greater than a first number threshold and first angles each between a corresponding one of all of the valid lines and a first coordinate axis of the target image are less than a first angle threshold (Zhao, Abstract with ¶0137 - ¶0140 – maximum and maximum thresholds are used for determining whether angular changes corresponding to fingers represent valid or invalid gesture inputs. ¶0127-¶0129 – multiple fingers may be required for performing certain gestures. ¶0139-¶0142, ¶0187 – if the angular change corresponding to each finger is below a threshold, relatively little movement is recognized, and no new gesture is detected),
determining a subsequent image of the target image as the target image, and returning to the step of determining at least two lines corresponding to the fingers in the target image until the first number is not greater than the first number threshold or one or more of the first angles are not less than the first angle threshold (Zhao, Fig. 3 Element S202 with ¶0103, ¶0113 – vectors obtained from first and second images. ¶0141 – a minimum threshold may be applied to an image in which the gesture is recognized);
determining, according to coordinate values of key points on the valid lines in the first image and a second image, a relative movingcoordinates along coordinate axes of each joint point (key points) are used to determine changes in linear regression determination coefficient. Gesture movement is obtained in part via comparison of coefficient and coefficient threshold);
recognizing, according to the relative moving distance, a gesture corresponding to changing from the first image to the second image (Zhao, ¶0138-¶0139, ¶0165-¶0166 – recognizing the gesture based on a change in the images).
However, Zhao appears not to expressly disclose the limitations shown in strikethrough above. However, in the same field of endeavor, Chung discloses finger gesture detection (Chung, Abstract and ¶0058), including
a relative moving distance of the human hand in a direction of the first coordinate axis, wherein the second image is a previous image of the target image (Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0066, ¶0083, ¶0177-¶0183, ¶0221 – additional frames used for gesture identification beyond two. Fig. 4E with ¶0126-¶0127 – three coordinate axes are used to track movement of the user’s fingers).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture detection of Zhao to include motion distance and additional images based on the teachings of Chung. The motivation for doing so would have been to enable a wider of variety of gestures to be detected, including gestures based on motion distance (Chung, ¶0212), and to enable the user to re-enter a gesture, or to detect a subsequent gesture (Chung, ¶0177-¶0183, ¶0218, ¶0221).
Regarding claim 2, Zhao as modified discloses the elements of claim 1 above, and further discloses wherein determining valid lines from the at least two lines comprises: calculating, for each first target line of the at least two lines, second angles each between the first target line and another line of the at least two lines other than the first target line (Zhao, ¶0234-¶0235 – vectors representing finger segments are used to calculate the angle between the finger segments. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers);
determining, under a condition that all of the second angles are greater than a second angle threshold, the first target line as an invalid line (Zhao, ¶0141, ¶0236 – total angular change is compared against a preset angular threshold to determine that the finger does not correspond to the specified gesture movement. In particular, some finger movement exceeding a threshold prevents the gesture from being recognized. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers. In an example, if the second total angular change is not less than the second preset angular change, the user is not determined to perform the gesture movement);
determining lines from the at least two lines other than the invalid line as the valid lines (Zhao, ¶0141, ¶0236 – total angular change is compared against a preset angular threshold to determine that the finger does not correspond to the specified gesture movement. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers. In an example, if the first total angular change is greater than the first preset angular change, the first portion of the gesture requirement is satisfied).
Regarding claim 17, Zhao discloses an electronic device comprising: a processor; a memory; and programs or instructions stored on the memory and executable by the processor, wherein the programs or instructions, when executed by the processor, implement operations comprising (Zhao, ¶0258, ¶0268, ¶0273 – computer processor executing instructions stored in hardware memory):
acquiring an image sequence comprising a human hand, and taking a first image in the image sequence as a target image (Zhao, Fig. 1 with Abstract and ¶0103 - images of a user’s hand performing a gesture);
determining at least two lines corresponding to fingers in the target image (Zhao, Abstract – vectors representing finger angles);
determining valid lines from the at least two lines (Zhao, Abstract with ¶0137 - ¶0140 – thresholds are used for determining whether angular changes corresponding to figures represent valid or invalid gesture inputs);
under a condition that a first number of the valid lines is greater than a first number threshold and first angles each between a corresponding one of all of the valid lines and a first coordinate axis of the target image are less than a first angle threshold (Zhao, Abstract with ¶0137 - ¶0140 – maximum and maximum thresholds are used for determining whether angular changes corresponding to figures represent valid or invalid gesture inputs. ¶0127-¶0129 – multiple fingers may be required for performing certain gestures. ¶0139-¶0142, ¶0187 – if the angular change corresponding to each finger is below a threshold, relatively little movement is recognized, and no new gesture is detected),
determining a subsequent image of the target image as the target image, and returning to the step of determining at least two lines corresponding to the fingers in the target image until the first number is not greater than the first number threshold or one or more of the first angles are not less than the first angle threshold (Zhao, Fig. 3 Element S202 with ¶0103, ¶0113 – vectors obtained from first and second images. ¶0141 – a minimum threshold may be applied to an image in which the gesture is recognized);
determining, according to coordinate values of key points on the valid lines in the first image and a second image, a relative moving
recognizing, according to the relative moving distance, a gesture corresponding to changing from the first image to the second image (Zhao, ¶0138-¶0139, ¶0165-¶0166 – recognizing the gesture based on a change in the images).
However, Zhao appears not to expressly disclose the limitations shown in strikethrough above. However, in the same field of endeavor, Chung discloses finger gesture detection (Chung, Abstract and ¶0058), including
a relative moving distance of the human hand in a direction of the first coordinate axis, wherein the second image is a previous image of the target image (Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0066, ¶0083, ¶0177-¶0183, ¶0221 – additional frames used for gesture identification beyond two. Fig. 4E with ¶0126-¶0127 – three coordinate axes are used to track movement of the user’s fingers).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture detection of Zhao to include motion distance and additional images based on the teachings of Chung. The motivation for doing so would have been to enable a wider of variety of gestures to be detected, including gestures based on motion distance (Chung, ¶0212), and to enable the user to re-enter a gesture, or to detect a subsequent gesture (Chung, ¶0177-¶0183, ¶0218, ¶0221).
Regarding claim 18, Zhao as modified discloses a readable storage medium having programs or instructions stored thereon, wherein the programs or instructions, when executed by a processor, implement steps of the gesture recognition method according to claim 1 (Zhao, ¶0258, ¶0268, ¶0273 – computer processor executing instructions stored in hardware memory).
Regarding claim 19, Zhao as modified discloses the elements of claim 17 above, and further discloses wherein determining valid lines from the at least two lines comprises: calculating, for each first target line of the at least two lines, second angles each between the first target line and another line of the at least two lines other than the first target line (Zhao, ¶0234-¶0235 – vectors representing finger segments are used to calculate the angle between the finger segments. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers);
determining, under a condition that all of the second angles are greater than a second angle threshold, the first target line as an invalid line (Zhao, ¶0141, ¶0236 – total angular change is compared against a preset angular threshold to determine that the finger does not correspond to the specified gesture movement. In particular, some finger movement exceeding a threshold prevents the gesture from being recognized. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers. In an example, if the second total angular change is not less than the second preset angular change, the user is not determined to perform the gesture movement);
determining lines from the at least two lines other than the invalid line as the valid lines (Zhao, ¶0236 – total angular change is compared against a preset angular threshold to determine that the finger does not correspond to the specified gesture movement. ¶0135-¶0141 – process is repeated to determine a total angular change amount corresponding to additional fingers. In an example, if the first total angular change is greater than the first preset angular change, the first portion of the gesture requirement is satisfied).
Claim(s) 3-5, and 20-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Chung in further view of Peng.
Regarding claim 3, Zhao as modified discloses the elements of claim 1 above, and further discloses wherein determining, according to the coordinate values of the key points on the valid lines in the first image and the second image, the relative moving distance of the human hand in the direction of the first coordinate axis comprises: calculating first differences between coordinate components on the first coordinate axis of the coordinate values of the key points on the valid lines in the first image and the second image and a coordinate component of a target key point on the first coordinate axis, wherein the target key point is a
calculating second differences between coordinate components on a second coordinate axis of the coordinate values of the key points on the valid lines in the second image and a coordinate component of the target key point on the second coordinate axis; determining the relative moving distance according to the first differences and the second differences (Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0066, ¶0083, ¶0177-¶0183, ¶0221 – additional frames used for gesture identification beyond two. Fig. 4E with ¶0126-¶0127 – three coordinate axes are used to track movement of the user’s fingers).
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor Pen discloses gesture identification (Peng, Abstract, ¶0054, ¶0078-¶0079), including
a wrist key point (Peng, ¶0079 – wrist key point).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the key points of Zhao as modified to include wrist key points based on the teachings of Peng. The motivation for doing so would have been to improve the accuracy of modeling of the user’s gestures, and more effectively account for the flexibility of the user’s arm (Peng, ¶0079).
Regarding claim 4, Zhao discloses the elements of claim 3 above, and further discloses wherein determining the relative moving distance according to the first differences and the second differences comprises: calculating, for each first valid line in the first image and the second image, a first average value of the first differences corresponding to the first valid line; calculating, for each second valid line in the second image, a second average value of the second differences corresponding to the second valid line (Zhao, ¶0154-¶0157 with Equation 3 – average coordinate value calculated for detected points for each finger. ¶0187-¶0195 – normalization of differences in angles);
determining the relative moving distance according to the first average value and the second average value (Zhao, Equations 3-4 with ¶0152-¶0164, ¶0183 – coordinates along coordinate axes of each joint point are used to determine changes in position. Gesture movement is obtained in part via comparison of coefficient and coefficient threshold and angular change. Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0094-¶0096, ¶0126 – distance measured between a position of the finger and a reference point in the coordinate frame. In this case, the moving distance is the distance from the reference).
Regarding claim 5, Zhao discloses the elements of claim 4 above, and further discloses wherein determining the relative moving distance according to the first average value and the second average value comprises: calculating a third average value of third differences between first average values corresponding to the second image and first average values corresponding to the first image (Zhao, ¶0166-¶0169 – a regression coefficient may be calculated for a specified finger or fingers. ¶0174 – an average value of the coefficient may be used);
calculating a fourth average value of absolute values of fourth differences of second average values of every two adjacent valid lines in the second image (Zhao, ¶0166-¶0169 – a regression coefficient may be calculated for a specified finger or fingers. ¶0174 – an average value of the coefficient may be used. ¶0160 – absolute value of the difference may be used as the coefficient change amount);
determining the relative moving distance according to the third average value and the fourth average value (Zhao, ¶0165, ¶0167-¶0168 – finger movement determination is based on the coefficient change determination. See also ¶0189-¶0195).
Regarding claim 20, Zhao as modified discloses the elements of claim 17 above, and further discloses wherein determining, according to the coordinate values of the key points on the valid lines in the first image and the second image, the relative moving distance of the human hand in the direction of the first coordinate axis comprises: calculating first differences between coordinate components on the first coordinate axis of the coordinate values of the key points on the valid lines in the first image and the second image and a coordinate component of a target key point on the first coordinate axis, wherein the target key point is a
calculating second differences between coordinate components on a second coordinate axis of the coordinate values of the key points on the valid lines in the second image and a coordinate component of the target key point on the second coordinate axis; determining the relative moving distance according to the first differences and the second differences (Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0066, ¶0083, ¶0177-¶0183, ¶0221 – additional frames used for gesture identification beyond two. Fig. 4E with ¶0126-¶0127 – three coordinate axes are used to track movement of the user’s fingers).
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor Pen discloses gesture identification (Peng, Abstract, ¶0054, ¶0078-¶0079), including
a wrist key point (Peng, ¶0079 – wrist key point).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the key points of Zhao as modified to include wrist key points based on the teachings of Peng. The motivation for doing so would have been to improve the accuracy of modeling of the user’s gestures, and more effectively account for the flexibility of the user’s arm (Peng, ¶0079).
Regarding claim 21, Zhao discloses the elements of claim 20 above, and further discloses wherein determining the relative moving distance according to the first differences and the second differences comprises: calculating, for each first valid line in the first image and the second image, a first average value of the first differences corresponding to the first valid line; calculating, for each second valid line in the second image, a second average value of the second differences corresponding to the second valid line (Zhao, ¶0154-¶0157 with Equation 3 – average coordinate value calculated for detected points for each finger. ¶0187-¶0195 – normalization of differences in angles);
determining the relative moving distance according to the first average value and the second average value (Zhao, Equations 3-4 with ¶0152-¶0164, ¶0183 – coordinates along coordinate axes of each joint point are used to determine changes in position. Gesture movement is obtained in part via comparison of coefficient and coefficient threshold and angular change. Chung, ¶0095, ¶0192-¶0193, ¶0206-¶0215 – determining motion distance corresponding to a gesture. ¶0094-¶0096, ¶0126 – distance measured between a position of the finger and a reference point in the coordinate frame. In this case, the moving distance is the distance from the reference).
Regarding claim 22, Zhao discloses the elements of claim 21 above, and further discloses wherein determining the relative moving distance according to the first average value and the second average value comprises: calculating a third average value of third differences between first average values corresponding to the second image and first average values corresponding to the first image (Zhao, ¶0166-¶0169 – a regression coefficient may be calculated for a specified finger or fingers. ¶0174 – an average value of the coefficient may be used);
calculating a fourth average value of absolute values of fourth differences of second average values of every two adjacent valid lines in the second image (Zhao, ¶0166-¶0169 – a regression coefficient may be calculated for a specified finger or fingers. ¶0174 – an average value of the coefficient may be used. ¶0160 – absolute value of the difference may be used as the coefficient change amount);
determining the relative moving distance according to the third average value and the fourth average value (Zhao, ¶0165, ¶0167-¶0168 – finger movement determination is based on the coefficient change determination. See also ¶0189-¶0195).
Claim(s) 6 and 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Chung in further view of Peng in further view of Ahn.
Regarding claim 6, Zhao as modified discloses the elements of claim 5 above. However, Zhao as modified appears not to expressly disclose wherein determining the relative moving distance according to the third average value and the fourth average value comprises: determining a quotient of the third average value and the fourth average value as the relative moving distance.
However, in the same field of endeavor, Ahn discloses finger gesture recognition (Ahn, Abstract), including
determining a quotient of the third value and the fourth value as the relative moving distance (Ahn, Fig. 5 with ¶0055-¶0055 – calculating a ratio representing the relative degree of movement of fingers to recognize the gesture).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculation of the degree of finger movement of Zhao as modified to include a ratio based on the teachings of Ahn. The motivation for doing so would have been to reduce calculation errors in determination of the click event (Ahn, ¶0054-¶0055), and to more effectively isolate changes which can be directly compared against a preset threshold.
Regarding claim 23, Zhao as modified discloses the elements of claim 22 above. However, Zhao as modified appears not to expressly disclose wherein determining the relative moving distance according to the third average value and the fourth average value comprises: determining a quotient of the third average value and the fourth average value as the relative moving distance.
However, in the same field of endeavor, Ahn discloses finger gesture recognition (Ahn, Abstract), including
determining a quotient of the third value and the fourth value as the relative moving distance (Ahn, Fig. 5 with ¶0055-¶0055 – calculating a ratio representing the relative degree of movement of fingers to recognize the gesture).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculation of the degree of finger movement of Zhao as modified to include a ratio based on the teachings of Ahn. The motivation for doing so would have been to reduce calculation errors in determination of the click event (Ahn, ¶0054-¶0055), and to more effectively isolate changes which can be directly compared against a preset threshold.
Claim(s) 7-8, and 24-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Chung in further view of Peng in further view of Ahn in further view of Yang.
Regarding claim 7, Zhao as modified discloses the elements of claim 6 above, and further discloses wherein the first coordinate axis is an X axis of the image, and the second coordinate axis is a Y axis of the image (Chung, Fig. 4E with ¶0126-¶0127 – x,y,z coordinate axes are used to track movement of the user’s fingers);
recognizing, according to the relative moving distance, the gesture corresponding to changing from the first image to the second image comprises: under a condition that an absolute value of the relative moving distance is greater than a preset distance threshold and the relative moving distance is greater than 0,
under a condition that the absolute value of the relative moving distance is greater than the preset distance threshold and the relative moving distance is
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Yang discloses recognizing gesture inputs (Yang, Abstract with ¶0005-¶0008), including
the relative moving distance is greater than 0, recognizing the gesture as a right-dial gesture and the relative moving distance is less than 0, recognizing the gesture as a left-dial gesture (Yang, Figs. 3A-3B with ¶0004-¶0010 and ¶0038-¶0039 – Clockwise, movement results in a movement angle greater than zero, corresponds to a downward/rightward input. Counter-clockwise, movement results in a movement angle less than zero, and corresponds to an upward/leftward input. See also Figs. 4A-4B, 6 with ¶0040-¶0041 and ¶0047-¶0058 – clockwise/counterclockwise rotational inputs).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture determination of Zhao as modified to include dialing gestures based on the teachings of Yang. The motivation for doing so would have been to facilitate rotational inputs for software object manipulation (Yang, ¶0006).
Regarding claim 8, Zhao as modified discloses the elements of claim 6 above, and further discloses wherein the first coordinate axis is a Y axis of the image, and the second coordinate axis is an X axis of the image (Chung, Fig. 4E with ¶0126-¶0127 – x,y,z coordinate axes are used to track movement of the user’s fingers);
recognizing, according to the relative moving distance, the gesture corresponding to changing from the first image to the second image comprises: under a condition that an absolute value of the relative moving distance is greater than a preset distance threshold and the relative moving distance is greater than 0,
under a condition that the absolute value of the relative moving distance is greater than the preset distance threshold and the relative moving distance is less than 0,
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Yang discloses recognizing gesture inputs (Yang, Abstract with ¶0005-¶0008), including
the relative moving distance is greater than 0, recognizing the gesture as a right-dial gesture and the relative moving distance is less than 0, recognizing the gesture as a left-dial gesture (Yang, Figs. 3A-3B with ¶0007 and ¶0038-¶0039 – downward, clockwise, movement results in a movement angle greater than zero, and turns the dial downward. Upward, counter-clockwise, movement results in a movement angle less than zero, and turns the dial upward. See also Figs. 4A-4B, 6 with ¶0040-¶0041 and ¶0047-¶0058 – clockwise/counterclockwise rotational inputs).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture determination of Zhao as modified to include dialing gestures based on the teachings of Yang. The motivation for doing so would have been to facilitate rotational inputs for software object manipulation (Yang, ¶0006).
Regarding claim 24, Zhao as modified discloses the elements of claim 23 above, and further discloses wherein the first coordinate axis is an X axis of the image, and the second coordinate axis is a Y axis of the image (Chung, Fig. 4E with ¶0126-¶0127 – x,y,z coordinate axes are used to track movement of the user’s fingers);
recognizing, according to the relative moving distance, the gesture corresponding to changing from the first image to the second image comprises: under a condition that an absolute value of the relative moving distance is greater than a preset distance threshold and the relative moving distance is greater than 0,
under a condition that the absolute value of the relative moving distance is greater than the preset distance threshold and the relative moving distance is
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Yang discloses recognizing gesture inputs (Yang, Abstract with ¶0005-¶0008), including
the relative moving distance is greater than 0, recognizing the gesture as a right-dial gesture and the relative moving distance is less than 0, recognizing the gesture as a left-dial gesture (Yang, Figs. 3A-3B with ¶0004-¶0010 and ¶0038-¶0039 – Clockwise, movement results in a movement angle greater than zero, corresponds to a downward/rightward input. Counter-clockwise, movement results in a movement angle less than zero, and corresponds to an upward/leftward input. See also Figs. 4A-4B, 6 with ¶0040-¶0041 and ¶0047-¶0058 – clockwise/counterclockwise rotational inputs).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture determination of Zhao as modified to include dialing gestures based on the teachings of Yang. The motivation for doing so would have been to facilitate rotational inputs for software object manipulation (Yang, ¶0006).
Regarding claim 25, Zhao as modified discloses the elements of claim 23 above, and further discloses wherein the first coordinate axis is a Y axis of the image, and the second coordinate axis is an X axis of the image (Chung, Fig. 4E with ¶0126-¶0127 – x,y,z coordinate axes are used to track movement of the user’s fingers);
recognizing, according to the relative moving distance, the gesture corresponding to changing from the first image to the second image comprises: under a condition that an absolute value of the relative moving distance is greater than a preset distance threshold and the relative moving distance is greater than 0,
under a condition that the absolute value of the relative moving distance is greater than the preset distance threshold and the relative moving distance is
However, Zhao as modified appears not to expressly disclose the limitations in strikethrough above. However, in the same field of endeavor, Yang discloses recognizing gesture inputs (Yang, Abstract with ¶0005-¶0008), including
the relative moving distance is greater than 0, recognizing the gesture as a right-dial gesture and the relative moving distance is less than 0, recognizing the gesture as a left-dial gesture (Yang, Figs. 3A-3B with ¶0007 and ¶0038-¶0039 – downward, clockwise, movement results in a movement angle greater than zero, and turns the dial downward. Upward, counter-clockwise, movement results in a movement angle less than zero, and turns the dial upward. See also Figs. 4A-4B, 6 with ¶0040-¶0041 and ¶0047-¶0058 – clockwise/counterclockwise rotational inputs).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the gesture determination of Zhao as modified to include dialing gestures based on the teachings of Yang. The motivation for doing so would have been to facilitate rotational inputs for software object manipulation (Yang, ¶0006).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. References are at least relevant as indicated in the corresponding summary.
Josephson et al. (US Patent Application Publication 2017/0180336) – determining an average of change in gesture position, velocity, and acceleration over time.
Nakasu et al. (US Patent Application Publication 2013/0321261) – average shaking or moving speed used to normalize inputs.
Alvarez (US Patent Application Publication 2013/0203360) – normalization of the gesture distance based on ratio of distance.
Touma et al. (US Patent Application Publication 2016/0229052) – angular threshold for gesture recognition from vector inputs.
Zhang et al. (US Patent Application Publication 2023/0135255) – moving-average filter for gesture inputs.
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/DANIEL W PARCHER/Primary Examiner, Art Unit 2174
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