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 .
Allowable Subject Matter
Claim 11 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.
Response to Arguments
Applicant's arguments filed 2/27/2026 have been fully considered but they are not persuasive.
Regarding the rejection under 35 USC § 101 of claim 17, the rejections is withdrawn.
Regarding the rejections under 35 USC § 102 of claim 1,16 and 17 applicant argues that Alghamdi(US 2013/0329982 A1) fails to anticipate the claims due to the reasons labeled A, B and C.
Regarding A. “ a perceptual model configured to simulate a sensor that perceives an object by electromagnetic waves” applicant states that “Alghamdi consistently refers to ‘radiological simulation’ and ‘radiological imaging,’ not perception. The distinction is meaningful: Alghamdi’s system does not simulate a sensor perceiving an object; it simulates radiation propagating through an object.” According to the claim language “perceives an object by electromagnetic waves” encompasses sensing, detecting, imaging, or otherwise obtaining information about an object using electromagnetic radiation. Radiological imaging uses electromagnetic radiation, such as X-rays that interact with an object and are detected to generate image information representing the object. Therefore, the simulated radiological imaging system simulates a sensor that perceives the object by electromagnetic waves, aligning with the claim element.
Regarding B. “input data including at least one of a propagation direction of the electromagnetic waves and spectral information about the electromagnetic waves” applicant states that cited “source configuration parameters” do not constitute such input data according to the claim element. The cited parameters "tube voltage," "tube current," "anode material," "target angle," and "filter material", "energy spectrum" and "angular distribution" define spectral information about the electromagnetic waves as according to the claim element. Further, applicate states that “claim 1 requires input data that includes ‘ a propagation direction of the electromagnetic waves and spectral information about the electromagnetic waves.” Claim 1 recites “at least one of” therefore, the reference only need disclose one of “a propagation direction” or the spectral information.
Regarding C. “output data that represents a result of perceiving the object” applicant states that Alghamdi’s describes images for observing the effects of simulation parameters, not output data representing a result of perceiving an object. The claim broadly recites “output data that represents a result of perceiving the object.” Alghamdi’s simulated images are output data. It represents the result of the simulated imaging sensor detecting radiation affected by the object. Since the image depicts internal structures of the object based on electromagnetic radiation passing through the object, it represents a result of perceiving or sensing the object. Internal structure is still part of the object. Therefore, output data representing internal structures is still output data representing a result of perceiving the object.
For at least the foregoing reasons, the rejection of claim 1 is sustained.
Independent claims 16 and 17 recite corresponding limitations and their rejections are sustained for the same reasons.
Regarding rejections under 35 USC § 103, claims 2-10 and 12-15, since these dependent claims relied on Alghamdi for limitations of the independent claim 1, and the rejection of independent claim 1 is sustained, the rejection for claims 2-7 and 12-15 are also sustained.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1,16,17 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Alghamdi (US-20130329982-A1)
Regarding claim 1, Alghamdi discloses An information processing device (para. [0036] “The virtual components are implemented in one or more data processing apparatus such as a computer workstation or general purpose computer.” Explicit disclosure of a “data processing apparatus”) comprising a perceptual model configured to simulate a sensor that perceives an object by electromagnetic waves (para. [0063] “The simulator then tracks the photons through the geometry using a combination of Monte Carlo and deterministic techniques such as ray tracing. For deterministic techniques, a pixel value in the imager is proportional to the sum of the linear attenuation coefficients along the path from the x-ray source to the pixel. Pixel values are computed one after another. In contrast, Monte Carlo simulation calculates the pixel value in a random fashion because the virtual photon arrives at a pixel randomly.” This passage teaches a data processing apparatus containing an image simulator that simulates radiological imaging by propagating photons from a source to an imager, and producing a simulated image by tallying photons at detector pixels. This is in essence a perceptual model that simulates a sensor which perceives an object via electromagnetic waves.) and generate output data that represents a result of perceiving the object (para. [0065] “The simulated image is generated from the scoring of the virtual photons arriving at the imager. An image is a collection of the number of photons arriving at each detector pixel in real life. In a virtual simulation, the average number of photons arriving at each detector pixel is calculated. Thus, realistic simulated images can be generated that allow users to observe the effect of patient posture and their choice of radiation source and imager.” The simulator produces image data that directly represents what the sensor would perceives.) on the basis of input data including at least one of a propagation direction of the electromagnetic waves and spectral information about the electromagnetic waves (para. [0059] “The imaging parameter data is set by the user using the interface 20 of FIG. 2. For example, in x-ray based methods, including CT, users may choose the tube voltage (kVp), the tube current (mAs), the anode material, the target angle and the filter material. From these data, the energy spectrum and the angular distribution of the x-ray beam can be computed. Other imaging parameter data settings may include centering point, Source Surface Distance (SSD normally fixed at 100 cm or 80 cm) and collimation. The imaging parameter data will be transmitted via the graphic interface to position the source direction data and the position of the virtual phantom in the Monte Carlo simulation process, as discussed in more detail below.” This passage shows that the simulator accepts imaging parameter data from which it computes, the energy spectrum (electromagnetic waves) and angular distribution (propagation direction)).
Claims 16, 17 which are similar in scope to claim 1, thus rejected under the same rationale.
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) 2-7,12-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Alghamdi in view of Goodenough (Goodenough, Adam A., and Scott D. Brown. "DIRSIG5: Next-generation remote sensing data and image simulation framework." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10.11 (2017): 4818-4833.).
Regarding claim 2, Alghamdi discloses all the elements of claim 1 as discussed above. However, Alghamdi does not disclose wherein the perceptual model includes an imager model configured to simulate an imager, the input data includes incident light data that includes at least one of an incident direction of an incident light and spectral information about the incident light for each pixel, and the imager model generates image data on the basis of the incident light data.
Goodenough does disclose wherein the perceptual model includes an imager model configured to simulate an imager (page. 4822, section B “The DIRSIG5 framework uses an application program interface (API) to define the basic interface between the radiometry core, the scheduler, and one or more sensors being modeled during a given simulation… Imaging sensors can feature multiple parametrically defined focal planes with data-driven spectral response and point-spread function (PSF) descriptions. The key capability of a sensor model plugin is the implementation of the function that generates the rays used to initiate paths in the path tracer. This function will be called by the radiometry core to start new paths until the pixel radiance has convergence based on criteria specified by the sensor plugin. The resulting spectral radiance is then processed by the sensor plugin (e.g., converted into signal) and written to an output data stream.” The sensor model plugin taught in this reference is an imager model. This defines imaging sensor characteristics and simulates image formation by generating sensor rays and producing signales.), the input data includes incident light data that includes at least one of an incident direction of an incident light and spectral information about the incident light for each pixel (page. 4283, para. 1-3 “At the start of the simulation, the scheduler will collect the spectral states (a wavelength window and a reference wavelength used for sampling) from all the sensor plugins… A capture is decomposed into a set of radiometric problems, which are generally analogous to pixels. The radiance for a pixel is generated in the radiometry core as an accumulation of radiances computed by the core path tracer… In order for the radiometry core to initiate paths in the path tracer for each problem, the scheduler provides the pipeline with access to the sensor plugin’s ray generation callback function. This callback function will generate initial path rays for the pixel indicated by a unique pixel problem index.” These passages tie together spectral information and incident direction per pixel. The scheduler decomposes each capture into pixel-analogous problems and then generates rays for the pixel while operating under collected spectral stares, the input to the imager model includes per-pixel incident light data with direction and spectral components.), and the imager model generates image data on the basis of the incident light data (page. 4823, para. 2-3 “A capture is decomposed into a set of radiometric problems, which are generally analogous to pixels. The radiance for a pixel is generated in the radiometry core as an accumulation of radiances computed by the core path tracer. The sensor plugin can specify the minimum number of paths… During the simulation, the scheduler iterates through these blocks of pixel problems, feeds them to the core radiometry pipeline, and routes the computed pixel radiances back to the sensor model for processing” The imager model, takes the per-pixel incident radiances and converts them into signal, producing output image data.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a yield a system that improves realism for imaging scenarios.
Regarding claim 3, the combination of Alghamdi and Goodenough disclose all the elements of claim 2 as discussed above. Goodenough also discloses wherein the incident light data includes at least one of the incident direction of the light incident on each pixel and the spectral information about the incident light during an exposure period (page. 4822, para. 6, “The pixel sampling function in the default plugin uses a variety of spatial and temporal sampling techniques to introduce common artifacts observed in remote sensing systems. Sample rays are constructed by randomly sampling the pixel area and offsetting those locations by importance sampling the (optional) PSF. The temporal integration of the detectors is modeled by distributing the sample ray times across the integration time window;” page. 4822, para. 4, “In order for the radiometry core to initiate paths in the path tracer for each problem, the scheduler provides the pipeline with access to the sensor plugin’s ray generation callback function. This callback function will generate initial path rays for the pixel indicated by a unique pixel problem index” These passages disclose how the model performs per-pixel sampling by treating each pixel as a radiometric problem and generating initial path rays for that pixel (incident directions of light) on each pixel. Those rays are then time-sampled across integration time window (exposure period), thus aligning with the claim element.) The motivation for combining both references discussed in claim 2 is incorporated herein.
Regarding claim 4, the combination of Alghamdi and Goodenough disclose all the elements of claim 3 as discussed above. Goodenough also discloses wherein the imager model notifies a rendering model that generates the input data of information related to the exposure period for each pixel(page. 4822, para. 6 “The pixel sampling function in the default plugin uses a variety of spatial and temporal sampling techniques to introduce common artifacts observed in remote sensing systems. Sample rays are constructed by randomly sampling the pixel area and offsetting those locations by importance sampling the (optional) PSF. The temporal integration of the detectors is modeled by distributing the sample ray times across the integration time window;” page. 4823, para. 4“In order for the radiometry core to initiate paths in the path tracer for each problem, the scheduler provides the pipeline with access to the sensor plugin’s ray generation callback function. This callback function will generate initial path rays for the pixel indicated by a unique pixel problem index. In addition to the geometric ray, the sensor plugin callback function will also supply the initial time. Variations in this time are commonly used by the sensor plugins to perform temporal sampling in order to model the integration time for a focal plane.” This reference teaches the imager model (sensor plugin) and the rendering model (radiometry core/path tracer.) The sensor’s plugin’s per-pixel ray-generation callback convey timing information supplying the initial time and distributes ray times across the integration time window (exposure period). This means that the imager model is notifying the rendering pipeline of exposure-period information for each pixel so the radiometry core can generate the pixel’s input data accordingly.) The motivation for combining both references discussed in claim 2 is incorporated herein.
Regarding claim 5, the combination of Alghamdi and Goodenough disclose all the elements of claim 3 as discussed above. Goodenough also discloses wherein the imager model simulates a rolling shutter type imager(page. 4822, para. 3, “Flexible timing (read out) and integration options allow the user to model common remote sensing payloads ranging from 2- D framing array cameras with rolling shutters used in UASs and small satellite applications to modular SCA push brooms used in larger satellites including Landsat8, IKONOS, and WorldView 2/3/4” Explicit discloses of rolling shutter used.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a yield a system that allows for higher frame rates with simple readouts.
Regarding claim 6, the combination of Alghamdi and Goodenough disclose all the elements of claim 2 as discussed above. Goodenough also discloses wherein the incident light data includes intensity of the light incident on each pixel for each incident direction(Page. 4823, Section IV “The job of the radiometry core is to compute radiances arriving at a specified location from a specified direction” This passage includes computing radiances(an intensity measure) and from a specified direction aligning with the claim element). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a have a system that has more consistent imaging.
Regarding claim 7, the combination of Alghamdi and Goodenough disclose all the elements of claim 6 as discussed above. Goodenough also discloses wherein the incident light data includes spectral information (page. 4823, para. 1, “At the start of the simulation, the scheduler will collect the spectral states (a wavelength window and a reference wavelength used for sampling) from all the sensor plugins.” Disclosure of obtaining spectral states.) about the incident light on each pixel for each incident direction (page. 4823, Section IV “The job of the radiometry core is to compute radiances arriving at a specified location from a specified direction” This passage includes data from a specified direction aligning with the claim element). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a have a system that has more consistent imaging.
Regarding claim 12, the combination of Alghamdi and Goodenough disclose all the elements of claim 1 as discussed above. Goodenough also discloses wherein the input data includes intensity of the electromagnetic waves for each propagation direction (page. 4823, section IV “The job of the radiometry core is to compute radiances arriving at a specified location from a specified direction;” page. 4823, para. 2 “A capture is decomposed into a set of radiometric problems, which are generally analogous to pixels. The radiance for a pixel is generated in the radiometry core as an accumulation of radiances computed by the core path tracer.” This reference teaches radiance being the intensity measure of electromagnetic waves, and it is explicitly computed from a specified direction, thus aligning with the claim element.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a yield a system that improves realism for imaging scenarios.
Regarding claim 13, the combination of Alghamdi and Goodenough discloses all the elements of claim 12 as discussed above. Goodenough also discloses wherein the input data includes spectral information about the electromagnetic waves for each propagation direction(page. 4823, section IV, “The job of the radiometry core is to compute radiances arriving at a specified location from a specified direction… When the radiometry core is asked to compute a set of problems, the computation node (e.g., a CPU in a cluster) has been primed with a particular spectral and temporal state by the scheduler;” page. 4824, section C, “The spectral states (generated by the sensors) provide the reference wavelength (in addition to the wavelengths at which the radiometry should be evaluated) used to drive that decision—i.e., the spectral weighting function that is used for the sampling is based on the reference wavelength. As a result, highly dispersive scene simulations should use many narrow wavelength windows, while spectrally consistent scenes require far fewer. Note that the reference wavelength mechanism only affects “spatial” consideration (e.g., the choice of direction), and the corresponding math is performed spectrally across the state wavelengths.” This reference teaches computing direction-resolved radiance (from a specified direction) and does so under spectral states that define the wavelengths at which the radiometry is evaluated. This means that for each propagation direction the system evaluates radiance spectrally across the state wavelengths.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a yield a system that improves realism for imaging scenarios.
Regarding claim 14, the combination of Alghamdi and Goodenough disclose all the elements of claim 1 as discussed above. Goodenough also discloses further comprising a rendering model configured to simulate electromagnetic waves that propagate from a surrounding space to the sensor(page. 4819, section B – page. 4820“In contrast to the approach used in DIRSIG4, DIRSIG5 utilizes a unified path-tracing approach [14], where a backward ray from the camera is used to construct a single path through the scene to an originating source or terminating event (absorption). Each node along the path is a scattering event at a surface or in a medium. We refer to the construction of these paths as path generation, which utilizes stepwise ray tracing and surface or medium interactions. Once the path has been constructed, the radiance arriving at the start of the path (the pixel) is computed in a step we refer to as path processing, which entails stepwise propagation of radiance through the chain of events along the path. Because this method prioritizes creation of single-path connections through the scene, we refer to it as a “depth first approach to finding multibounce light paths between sources and the sensor (cf., Fig. 2).” This reference teaches the radiometry core as the rendering model, as discussed above. It explicitly stimulates EM-wave propagation (via path tracing of radiance) from the surrounding scene (“sources”) to the sensor, aligning with the claim element.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a reduce computing time while maintaining accuracy.
Regarding claim 15, Alghamdi discloses all the elements of claim 1 as discussed above. However, Alghambi does not fully disclose wherein the perceptual model simulates the sensor provided in a vehicle.
Goodenough does disclose wherein the perceptual model simulates the sensor provided in a vehicle (page. 4822, section B, para. 2 “The plugin utilizes a vehicle-centric (e.g., van, unmanned aircraft system (UAS), airplane, satellite, etc.) description and allows the user to define one or more imaging sensors or metadata collection instruments (e.g., platform location and orientation) that attach to the vehicle at various locations. Imaging sensors can feature multiple parametrically defined focal planes with data-driven spectral response and point-spread function (PSF) descriptions.” Explicit disclosure that the reference teaches simulating sensors mounter on vehicles.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Goodenough into the teachings of Alghamdi in order to a allow the system to achieve more realistic results when in a scenario that a vehicle is being used.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Alghamdi as modified by Goodenough as applied to claim 2 above, and further in view of Ebstyne (US-20200090398-A1).
Regarding claim 8, the combination of Alghamdi and Goodenough disclose all the elements of claim 2 as discussed above. However, the combination does not disclose wherein the spectral information has a greater number of bands than the number of bands in the imager model.
Ebstyne does disclose wherein the spectral information has a greater number of bands than the number of bands in the imager model(para.[0028] “For example, a certain simulation scenario may involve the use of 12 different specified spectral bands: RGB (three bands), plus three bands in each of IR, UV, and radio frequency (RF) spectral regions. However, rendering engine 190 can handle only three bands at a time, treating these three bands as RGB. ” This reference teaches using 12 spectral bands while the imager side operates on 3 bands(RGB) per pass, then merges passes to recover all bands. This means that the input specral information (of 12 bands) has more bands that the models band could(3).) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Ebstynne into the combination of teachings of Goodenough and Alghamdi in order to a have a system that can provide more realistic and consistent rendering with any input.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Alghamdi as modified by Goodenough as applied to claim 2 above, and further in view of Barnes (US-20170264833-A1).
Regarding claim 9, the combination of Alghamdi and Goodenough disclose all the elements of claim 2 as discussed above. However, the combination does not disclose wherein the spectral information has a band width which is greater than 0 nm and not more than 5 nm.
Barnes does disclose wherein the spectral information has a band width which is greater than 0 nm and not more than 5 nm (para.[0072] “Here, compared to a multi-spectral workflow, a hyperspectral workflow of images may include image data for a larger number of specified frequency bands (e.g., dozens of specified frequency bands for hyperspectral versus 4 bands for multi-spectral), and for specified spectral frequency bands having narrower bandwidths (e.g., 5 nm bandwidth channel for hyperspectral versus 50 nm bandwidth channels for multi-spectral), each spectral frequency band characterized by a central wavelength and a bandwidth (e.g., corresponding to a full width at half maximum value). For example, in some embodiments, each client device (or the client devices collectively) is configured to collect a hyperspectral workflow of images, where each image in the workflow is collected at a discrete spectral frequency band, and the workflow comprises images collected at any 4 or more, any 5 or more, any 6 or more, any 7 or more, any 10 or more, or any 20 or more different spectral bands. In some embodiments, corresponding full width at half maximum values are less than 30 nm, less than 20 nm, less than 15 nm, less than 10 nm, or 5 nm or less.” This patent teaches spectral bands with 5nm that first within the range detailed in the claim element.) It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teachings of Barnes into the combinations of teachings of in order to a allow for the system to work with spectral bands within a certain range.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Alghamdi as modified by Goodenough as applied to claim 2 above, and further in view of Hasinoff(US-20140347521-A1).
Regarding claim 10, the combination of Alghamdi and Goodenough disclose the elements of claim 2 as discussed above. However, the combination does not disclose wherein the imager model selects a function and a characteristic for the imager to be simulated on the basis of a scene to be simulated.
Hasinoff does disclose wherein the imager model selects a function (para. [0066] “Particularly, step 308 may include merging one or more of the images captured at step 306 in a combined image 310. Step 308 may also include forming a histogram 312 from the merged images, and then using the histogram, and possibly some or all of the information in training image data 304, to classify the scene (e.g., as an LDR scene or an HDR scene), determine the structure of the payload burst based on the classification of the scene, and determine the TETs to use when capturing images according to the payload burst.” This passage teaches selecting a function of the imager, whether to run an HDR burst fusion workflow or a LDR capture.) and a characteristic for the imager to be simulated on the basis of a scene to be simulated (para. [0050] “Camera devices may support an auto-exposure (AE) mode in which, prior to output image capture, the camera determines the TET based on the brightness of the scene.” The system selects a characteristic, in this case exposure time, based on scene brightness.)
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRIS ALEJANDRO PUNTIER whose telephone number is (703)756-1893. The examiner can normally be reached M-F 7:30-5:00.
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/CHRIS ALEJANDRO PUNTIER/ Examiner, Art Unit 2616
/DANIEL F HAJNIK/ Supervisory Patent Examiner, Art Unit 2616
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