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 Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: calculation unit, display unit, storage unit, virtual gold device, service device, in claims 10-13
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 3-4, and 10-12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Joo (US 20180221746).
Regarding claim 1:
Joo discloses: a method for detecting the spin of a ball in motion (¶ [0009] discloses a device and method for sensing a moving ball), comprising:
an image acquisition step of acquiring a first image of a ball at a first time and acquiring a second image of the ball at a second time (¶ [0010] discloses the device including an image acquirer for acquiring continuous images of the moving ball, an image processor for processing a first image and a second image continuously acquired by the image acquirer; ¶ [0051] explains that the first one of the continuously acquired images is a first image and the second one of the continuously acquired images is a second image. ¶ [0067] - ¶ [0068] disclose source images may be extracted from the two images continuously acquired at step S10);
the ball being in motion with spin and having an identifier (¶ [0013] Joo teaches a moving ball and the feature/identifier may be image edge information about dimples of the ball, a logo or a specific mark formed on the ball, or cracks or foreign matter on the ball. ¶¶ [0079] – [0080] also states that edge information may be from dimples, crack, or a logo or a specific mark);
an identification information acquisition step of acquiring first identification information of the identifier from the first image and acquiring second identification information of the identifier from the second image (¶¶ [0011] – [0012] Joo discloses detecting image edge information from a first ball image to generate first feature information and detecting image edge information from a second ball image to generate second feature information. ¶¶ [0014] – [0015] further teaches that the first/second feature information may include coordinate values and edge intensity values. ¶¶ [0086] – [0087] teaches that generated feature information includes coordinates of pixels and edge intensity values); and
a spin detection step of determining an estimated spin by using cumulative spin data (¶¶ [0052] – [0055] teach calculating a function value for determining whether it is suitable for information about a trial spin to be decided as final spin information using the result of applying trial spin to the first and second feature information, and teaches repeated spin data pf function values calculated by repeatedly applying the trial spin information a predetermined number of times. ¶ [0112] – [0117] provide trial rotation feature information and target feature information are compared to calculate similarity, the maximum similarity is selected, and the trial spin amount applied to the selected trial rotation feature information is decided as the finial spin. ¶¶ [0126] – [0127] also teach that the spin calculation process may be performed on all of the continuous images acquired by the camera or on only some of the continuous images acquired by the camera and pieces of spin information may be combined according to a predetermined function to calculate final spin information, and pieces of spin information having the highest similarity, among the calculated pieces of spin information, may be selected as final spin information);
and applying the estimated spin to the first and second identifier information to detect the spin of the ball in motion (¶ [0016] teaches a trial spin applicator that converts coordinates of pixels corresponding to the first feature information into 3D position information, applies trial spin information to that 3D position information, converts the pixels to 2D position information to generate trial rotation feature information, and compares edge intensity values of the trial rotation feature information with target feature information extracted from the second feature information to calculate similarity and decide final spin information. ¶ [0095] also teaches extracting and applying a trial axis and trial spin generate trial rotation feature information and target feature information. ¶ ¶ [0110] – [0113] also teach applying trial spin axis and trial spin amount to the first feature information, comparing the resulting trial rotation feature information with target feature information generated from the second feature information, and deciding final information about the trial spin axis and trial spin amount based on the selected similarity value).
Regarding claim 3:
Joo further teaches: wherein the ball is a golf ball, and as a user hits the golf ball with a golf club, the golf ball moves with spin (¶ [0037], and ¶¶ [0120] – [0121] disclose an image of golf ball hit by a user using a golf club, and the image is analyzed to calculate the spin of the hit ball);
wherein the method further comprises detecting a state change by the motion of the golf ball between the first time and the second time (¶¶ [0051], [0054] teach that the captured images are analyzed in pairs, where the first and second image are used to calculate the spin of the ball); and
wherein after spin data corresponding to the state change of the golf ball is determined (¶¶ [0052] – [0053] and [0110] – [0117] teach determining spin data corresponds to the state change from the first ball image to the second ball image),
the cumulative spin data is formed using the determined spin data (¶¶ [0126] – [0127] teaches that after the spin data for image pair state is determined, combined spin data is formed from these determined spin information pieces having the highest similarity or selecting the pieces of spin information having the highest similarity as final spin information).
Regarding claim 4:
Joo further teaches: wherein in the spin detection step, a result of applying the estimated spin to the first identification information is compared with the second identification information (¶¶ [0110] – [0112] teach trial spin axis/trial spin amount, which corresponds to estimates spin. The first feature information corresponds to first identification information, and target feature information corresponds to the second identification information);
and according to a result of comparing with the second identification information, the estimated spin is determined as the spin of the ball in motion (¶¶ [0013], [0116] - [0117], and [0053] after comparing trial rotation function information with target feature information, the maximum value of the calculated similarity is selected)
or a new estimated spin is determined and the spin detection step is performed again (¶ [0053] discloses that when a current trial spin is not selected as final, another trial spin is applied and the comparison is repeated until final spin is calculated).
Regarding claim 10:
Joo discloses: A virtual golf system (¶ [0004] teaches applying ball sensing device/method to virtual golf. Also see ¶¶ [0008], [0038] and [0129]) comprising:
a calculation unit to perform a calculation process of calculating a motion of a virtual golf ball corresponding to a real golf ball when a user hits the real golf ball (¶ [0002] discloses sensing the physical property of a mobbing ball hit by a golfer to analyze the hit ball or realize the hit ball as an image for simulation golf field such as screen golf. ¶ [0004] discloses that in a screen golf system, the ball hit according to the user’s gold wing is sensed to calculate trajectory of the ball and gold simulation is performed to realize virtual golf based thereon. Under BRI calculating trajectory of the ball in a virtual golf simulation reads on calculating a motion of a virtual golf);
a display unit to display a virtual golf course and the virtual golf ball moving in the virtual golf course as calculated in the calculation process (¶ [0002] discloses realizing the hit ball as an image for use in a simulation golf field such as screen golf. ¶ [0004] discloses that in a screen golf system, the ball hit according to the user’s gold wing is sensed to calculate trajectory of the ball and gold simulation is performed to realize virtual golf based thereon. ¶ [0129] discloses virtual golf through golf simulation based on virtual reality);
wherein the virtual golf device detects the spin of the real golf ball after the user hits the real golf ball by a method for detecting the spin of a ball in motion including an image acquisition step of acquiring a first image of the ball at a first time and acquiring a second image of the ball at a second time (¶ [0010] discloses the device including an image acquirer for acquiring continuous images of the moving ball, an image processor for processing a first image and a second image continuously acquired by the image acquirer; ¶ [0051] explains that the first one of the continuously acquired images is a first image and the second one of the continuously acquired images is a second image. ¶ [0067] - ¶ [0068] disclose source images may be extracted from the two images continuously acquired at step S10);
the ball being in motion with spin and having an identifier (¶ [0013] Joo teaches a moving ball and the feature/identifier may be image edge information about dimples of the ball, a logo or a specific mark formed on the ball, or cracks or foreign matter on the ball. ¶¶ [0079] – [0080] also states that edge information may be from dimples, crack, or a logo or a specific mark);
an identification information acquisition step of acquiring first identification information of the identifier from the first image and acquiring second identification information of the identifier from the second image (¶¶ [0011] – [0012] Joo discloses detecting image edge information from a first ball image to generate first feature information and detecting image edge information from a second ball image to generate second feature information. ¶¶ [0014] – [0015] further teaches that the first/second feature information may include coordinate values and edge intensity values. ¶¶ [0086] – [0087] teaches that generated feature information includes coordinates of pixels and edge intensity values); and
a spin detection step of determining an estimated spin by using cumulative spin data (¶[0052] – [0055 teach calculating a function value for determining whether it is suitable for information about a trial spin to be decided as final spin information using the result of applying trial spin to the first and second feature information, and teaches repeated spin data pf function values calculated by repeatedly applying the trial spin information a predetermined number of times. ¶ [0112] – [0117] provide trial rotation feature information and target feature information are compared to calculate similarity, the maximum similarity is selected, and the trial spin amount applied to the selected trial rotation feature information is decided as the finial spin. ¶¶ [0126] – [0127] also teach that the spin calculation process may be performed on all of the continuous images acquired by the camera or on only some of the continuous images acquired by the camera and pieces of spin information may be combined according to a predetermined function to calculate final spin information, and pieces of spin information having the highest similarity, among the calculated pieces of spin information, may be selected as final spin information);
and applying the estimated spin to the first and second identifier information to detect the spin of the ball in motion (¶ [0016] teaches a trial spin applicator that converts coordinates of pixels corresponding to the first feature information into 3D position information, applies trial spin information to that 3D position information, converts the pixels to 2D position information to generate trial rotation feature information, and compares edge intensity values of the trial rotation feature information with target feature information extracted from the second feature information to calculate similarity and decide final spin information. ¶ [0095] also teach extracting and applying a trial axis and trial spin generate trial rotation feature information and target feature information. ¶ ¶ [0110] – [0113] also teaches applying trial spin axis and trial spin amount to the first feature information, comparing the resulting trial rotation feature information with target feature information generated from the second feature information, and deciding final information about the trial spin axis and trial spin amount based on the selected similarity value).
Regarding claim 11:
Joo discloses: wherein the calculation process reflects a result of detecting the spin of the real golf ball (¶¶ [0002], [0003], [0004], [0008], [0010] – [0016] teach that virtual golf process calculates the trajectory of the virtual ball using sensed physical properties and the sensing method detects the spin of the real golf ball as one such physical property).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over by Joo (US 20180221746) in view of Nicora (US 20090191929).
Regarding claim 12:
A virtual golf system comprising: at least one virtual golf device (¶ [0004] teaches applying ball sensing device/method to virtual golf. Also see ¶¶ [0008], [0038] and [0129]) comprising:
a calculation unit to perform a calculation process of calculating a motion of a virtual golf ball corresponding to a real golf ball when a user hits the real golf ball (¶ [0002] discloses sensing the physical property of a mobbing ball hit by a golfer to analyze the hit ball or realize the hit ball as an image for simulation golf field such as screen golf. ¶ [0004] discloses that in a screen golf system, the ball hit according to the user’s gold wing is sensed to calculate trajectory of the ball and gold simulation is performed to realize virtual golf based thereon. Under BRI calculating trajectory of the ball in a virtual golf simulation reads on calculating a motion of a virtual golf);
a display unit to display a virtual golf course and the virtual golf ball moving in the virtual golf course as calculated in the calculation process (¶ [0002] discloses realizing the hit ball as an image for use in a simulation golf field such as screen golf. ¶ [0004] discloses that in a screen golf system, the ball hit according to the user’s gold wing is sensed to calculate trajectory of the ball and gold simulation is performed to realize virtual golf based thereon. ¶ [0129] discloses virtual golf through golf simulation based on virtual reality);
wherein the virtual golf device detects the spin of the real golf ball after the user hits the real golf ball by a method for detecting the spin of a ball in motion including an image acquisition step of acquiring a first image of the ball at a first time and acquiring a second image of the ball at a second time (¶ [0010] discloses the device including an image acquirer for acquiring continuous images of the moving ball, an image processor for processing a first image and a second image continuously acquired by the image acquirer; ¶ [0051] explains that the first one of the continuously acquired images is a first image and the second one of the continuously acquired images is a second image. ¶ [0067] - ¶ [0068] disclose source images may be extracted from the two images continuously acquired at step S10);
the ball being in motion with spin and having an identifier (¶ [0013] Joo teaches a moving ball and the feature/identifier may be image edge information about dimples of the ball, a logo or a specific mark formed on the ball, or cracks or foreign matter on the ball. ¶¶ [0079] – [0080] also states that edge information may be from dimples, crack, or a logo or a specific mark);
an identification information acquisition step of acquiring first identification information of the identifier from the first image and acquiring second identification information of the identifier from the second image (¶¶ [0011] – [0012] Joo discloses detecting image edge information from a first ball image to generate first feature information and detecting image edge information from a second ball image to generate second feature information. ¶¶ [0014] – [0015] further teaches that the first/second feature information may include coordinate values and edge intensity values. ¶¶ [0086] – [0087] teaches that generated feature information includes coordinates of pixels and edge intensity values); and
a spin detection step of determining an estimated spin by using cumulative spin data (¶[0052] – [0055 teach calculating a function value for determining whether it is suitable for information about a trial spin to be decided as final spin information using the result of applying trial spin to the first and second feature information, and teaches repeated spin data pf function values calculated by repeatedly applying the trial spin information a predetermined number of times. ¶ [0112] – [0117] provide trial rotation feature information and target feature information are compared to calculate similarity, the maximum similarity is selected, and the trial spin amount applied to the selected trial rotation feature information is decided as the finial spin. ¶¶ [0126] – [0127] also teach that the spin calculation process may be performed on all of the continuous images acquired by the camera or on only some of the continuous images acquired by the camera and pieces of spin information may be combined according to a predetermined function to calculate final spin information, and pieces of spin information having the highest similarity, among the calculated pieces of spin information, may be selected as final spin information);
and applying the estimated spin to the first and second identifier information to detect the spin of the ball in motion (¶ [0016] teaches a trial spin applicator that converts coordinates of pixels corresponding to the first feature information into 3D position information, applies trial spin information to that 3D position information, converts the pixels to 2D position information to generate trial rotation feature information, and compares edge intensity values of the trial rotation feature information with target feature information extracted from the second feature information to calculate similarity and decide final spin information. ¶ [0095] also teach extracting and applying a trial axis and trial spin generate trial rotation feature information and target feature information. ¶ ¶ [0110] – [0113] also teaches applying trial spin axis and trial spin amount to the first feature information, comparing the resulting trial rotation feature information with target feature information generated from the second feature information, and deciding final information about the trial spin axis and trial spin amount based on the selected similarity value).
Joo does not specifically teach a service connected to the virtual golf device via communication.
However, in the same field of endeavor, Nicora teaches: a service connected to the virtual golf device via communication (¶ [0024] discloses FIG. 1, a simulator network is shown. Common characteristics of a simulator network include a scoring computer 105, and a web server 106. ¶ [0025] adds that the golf simulators 101, 102, the user computers 103, 104, the scoring computer 105, and the web server 106 are connected to a WAN 100 by computer network protocols and devices. ¶ [0011] further discloses a web enabled physical golf simulator configured to transmit indoor golf performance data over a computer network during an indoor golf tournament. ¶ [0026 also discloses that golf simulators 101 will have a large display screen 807 that has an image of the golf hole 808 being played from the vantage point of the user's position 809. The golf ball 805 will strike the screen 807 after being hit by the club 806, and a variety of sensors will compute a golf ball trajectory based on the golf ball position, velocity, rotation, etc.).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Joo to incorporate the teachings of Nicora by including a networked golf simulator architecture in order to allow Joo’s spin detecting virtual golf devices to operate in a conventional networked virtual golf system with centralized scoring functionality.
Regarding claim 13:
Nicora further teaches: wherein the service device includes a storage unit to store user information (¶ [0036] discloses a plurality of users can play from the same golf simulator 101, 102, or from different golf simulators 101, 102. In some embodiments, as each user completes a hole, data about the score for the hole is uploaded from the golf simulators 101, 102 to the scoring computer 105. The scoring computer 105 is configured to interpret the data received in order to score and record information about the tournament and to rate and record information about the players. ¶ [0037] further discloses that the user computers 103, 104 can access scoring, ranking, and statistical information about ongoing and completed tournaments stored on the scoring computer 105, and/or the web server 106).
wherein the user information is used to form the cumulative spin data during the detection of the spin of the real golf ball (Joo teaches forming cumulative spin data during spin detection (see Joo ¶¶ [0051] – [0055], [0110] – [0117], and [0126] – [0127]). Nicora teaches using stored user information in the networked virtual golf system (See Nicora ¶ [0033] where players can be added to the tournaments)).
Claim(s) 2 is rejected under 35 U.S.C. 103 as being unpatentable over by Joo (US 20180221746) in view of Niegowski (US 20170232296).
Regarding claim 2:
Joo further teaches: wherein the ball is a golf ball, and as a user hits the golf ball with a golf club, the golf ball moves with spin (¶ [0037], and ¶¶ [0120] – [0121 disclose an image of golf ball hit by a user using a golf club, and the image is analyzed to calculate the spin of the hit ball); and
wherein the cumulative spin data is formed using information associated with the spin of the golf ball (¶¶ [0052] – [0055] disclose trial spin/function value process. ¶¶ [0126] – [0127] plurality of pieces of spin information may be calculated from plural image pairs and combined, averaged, or selected);
Joo does not specifically teach: when the user who hits the golf ball of which the spin is currently to be detected and other users having a same golf skill level as the corresponding user have played golf in the past.
However, in the same field of endeavor, Niegowski teaches that golf data includes spin information (see Niegowski ¶¶ [0008], [0009], [0158] – [0159]).
Niegowsky further teaches: when the user who hits the golf ball of which the spin is currently to be detected (¶ [0141] – [0142] further discloses that the stored information may come from the player using the system including information downloaded from a previous time playing a hole, and that advice may account for the player’s previous history. ¶¶ [0146] – [0148] further teach collecting, storing, and using golf swing dynamics information and ball flight information for one or more swings made by a player, including user ID and handicap, and uploading swing dynamics and ball flight data to a central gold data hub);
and other users having a same golf skill level as the corresponding user have played golf in the past (¶ [0056] teaches information displayed may compare the first golfer’s data with corresponding data from other community members, including golfers having a handicap within a predetermined range of a handicap of the first golfer, and golfers of a similar skill lever that have played the same course. ¶ [0141] further teaches tip information may originate from another player of similar skill lever (similar handicap) that previously played the course, from another player having similar swing speed, similar composite gold swing signature, or similar typical ball flight. ¶ [0149] also teaches comparing swing data of the current golfer against similar swing data for others to locate a match).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Joo to incorporate the teachings of Niegowsky by including storing individual and community golf data in order to improve the spin detection by using the stored spin associated data from the current golfer and golfer of similar skills to initialize the spin information used during detection, thereby reducing the search and calculation burden and improving accuracy.
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over by Joo (US 20180221746) in view of Ijiri (US 20180174308).
Regarding claim 8:
While Joo teaches that although spin information may be calculated using two continuously acquired images, the spin calculation process may alternatively be performed on all of the continuous images acquired by the camera or only some of the continuous images acquired by the camera ( Joo ¶ [0126]).
Nonetheless, in the same field of endeavor, Ijiri teaches: performing additional steps including a step of acquiring a third image of the ball at a third time (¶ [0011] teaches acquiring a template image from any of multiple frames of a video in which the spherical body captured; ¶ [0012] teaches acquiring multiple clipped images by extracting similar regions from each of the multiple frames; and ¶ [0045] teaches acquiring a series of clipped images from multiple frames);
a step of acquiring third identification information of the identifier from the third image (Joo in ¶¶ [0086] – [0092] teaches that feature information generated from ball images includes coordinates of pixels and edge intensity values, and that first and second feature information are generated from the first and second ball images. Ijiri also teaches extracting multiple clipped images of the spherical body from multiple video frames, where the clipped images render the spherical body in the same size and position, and then calculates similarity/dissimilarity between those multiple clipped images based on pixel value differences or vector similarity (Ijiri ¶¶ [0045] – [0051]). Under BRI, Ijiri’s pixel/image information from a third clipped image corresponds to third identification information because it is image derived information identifying the surface state/feature of the ball in that later frame. Joo also teaches using such feature information as the identifier/feature information for spin detection);
and a step of verifying the detected spin by using the third identification information (Ijiri ¶¶ [0013] – [0014], [0048] – [0052] teach calculating similarities/dissimilarities between multiple clipped images and arranging the calculated similarities/dissimilarities in the shooting order of the frames, then estimating spin from the distribution of the elements in the similarity/dissimilarity matrix. ¶¶ [0093] – [0094] teach that the estimator may estimate the spin period by multiple different methods and if the same value T is obtained by all the methods, this means that the measurement result of the spin period is highly accurate. ¶ [0113] teaches outputting estimated spin factors including spin period, spin rate, and spin axis direction).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Joo to incorporate the teachings of Ijiri by including multi frame similarity/dissimilarity verification in order to improve spin measurement reliability by comparing image similarities/dissimilarities over frame order. The combination would predictably improve confidence in Joo’s detected spin by using a third/later image to verify that the detected spin remains consistent with the ball’s later observed surface/feature state.
Allowable Subject Matter
Claims 5-7 and 9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WASSIM MAHROUKA whose telephone number is (571)272-2945. The examiner can normally be reached Monday-Thursday 8:00-5:00 EST.
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/WASSIM MAHROUKA/Primary Examiner, Art Unit 2665
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