DETAILED ACTION
This Action addresses the communication received on 7 Nov 2025. Applicant has amended Claims 1, 9, and 16; and previously cancelled Claims 8, 15, and 18. The Office rejects pending Claims 1-7, 9-14, 16-17, 19-23 as detailed below.
Response to Amendments
Claim Rejections - 35 USC § 112
Based on Applicant’s amendment to the claims, the Office withdraws the indefiniteness [112(b)] rejection to Claims 9-10 and any corresponding dependent claims.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 7, 9-10 and 22-23 remain rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor at the time the application was filed, had possession of the claimed invention.
In particular the claims recite “pre-optimizing,” generating a target region image with, and updating/calibrating (i.e., training) a deep neural network. However, the disclosure conspicuously lacks any technical information as to the set-up, configuration, and incorporation of a deep neural network into the claimed invention. Only a single figure in the drawings even mentions deep neural networks and that comprises merely two text boxes in a flowchart sequence. The complete lack of detail present in the disclosure for purportedly incorporating a complex AI component into a 3D Lidar system would not reasonably convey to one skilled in the art that Applicant had possession of the claimed invention at the time of filing.
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.
Claims 1-6, 11, 13-14, 16-17, and 19-21 are rejected under 35 U.S.C. 103 as unpatentable over Schmidt et al. (U.S. Pub. 20190208183) in view of Amirsolaimani et al. (U.S. Pat. 11044460):
As for Claim 1, Schmidt teaches at least a light source unit, configured to emit light pulses to illuminate a scene to be measured (Fig. 2, Illuminator 110, ¶25 L3-6; Flowchart Fig. 4, 402, ¶74 L2-5); at least an optical transmission unit, configured to control transmission of a reflected light obtained after the light pulses are reflected by an object in the scene to be measured (Fig. 2, Receiving optics 172, ¶44 L1-4); at least a photoreceptor unit, configured to receive a light transmitted through the optical transmission unit to perform imaging (Fig. 2, Sensor 170, ¶34 L4-7) and at least a processor unit, configured to control the light source unit, the optical transmission unit and the photoreceptor unit (Fig. 2, processor subsystem 140, ¶55), and to determine scene distance information of the scene to be measured based on an imaging result of the photoreceptor unit, wherein the light pulses comprise at least a first light pulse and a second light pulse (¶165 L1: “Each of the systems 104,450, 500, 1100, 1300 can be a LIDAR system for measuring distances to objects in a scene by illuminating those objects with a pulsed laser light, and then measuring the reflected pulses with a sensor. Differences in laser return times can be used to make digital 3D-representations [including scene distance information] of the target scene.”) […]. Schmidt does not directly teach the remaining limitations.
But Amirsolaimani teaches and a ratio of a first processed pulse envelope, which is obtained by processing a first pulse envelope of the first light pulse by the optical transmission unit, to a second processed pulse envelope, which is obtained by processing a second pulse envelope of the second light pulse by the optical transmission unit, is a monotonic function varying with time, such that an exposure amount ratio of two exposures by the first light pulse and the second light pulse is a monotonic function (Col. 6|45: “The detector pixel 200C of FIG. 2C also includes first 241 and second 242 sub-pixels having first 251 and second 252 wavelength dependencies of responsivity (i.e., responses to the first and second processed pulse envelopes) J, respectively. The responsivity 251 of the first sub-pixel 241 monotonically decreases with wavelength, and the responsivity 252 of the second sub-pixel 242 monotonically increases with wavelength within the infrared wavelength range defined by the emission spectrum 215 of the polychromatic light source 108. Notably, the responsivities 251, 252 of the first 241 and second 242 sub-pixels are non-zero across the entire infrared wavelength range. This enables one to avoid division by zero in case of determining the wavelength of the impinging light from a ratio of subpixel signals. Furthermore, an advantage of monotonic spectral responsivities within the wavelength range is that the ratio of the two responsivities is also monotonic, which may reduce uncertainty of wavelength determination, and, accordingly, uncertainty of the 3D position and shape of the object being imaged. More generally, at least two sub-pixels may be provided. Providing three or more sub-pixels may enable one to cover the required wavelength range more easily, as long as light at each wavelength within that wavelength range may be detected by at least two sub-pixels having different spectral shapes of responsivity.”)
It 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 to combine Schmidt and Amirsolaimani because it “may reduce uncertainty of wavelength determination, and, accordingly, uncertainty of the 3D position and shape of the object being imaged.” (Amirsolaimani, Col. 6|52)
As for Claim 2, which depends on Claim 1, Schmidt teaches wherein the light source unit is configured to simultaneously or sequentially emit light pulses of different wavelengths, different polarizations, and different spatial structures and/or different temporal structures (¶93 L1: “The light source 511 may also have elements that emit light at different wavelengths that can be combined by optical elements. Different wavelengths may also be emitted that can be used to differentiate some types of surfaces or materials based on the spectral properties of the object materials. Multiple wavelengths from the light source 511 can also reduce spatial or temporal coherence or may smooth or change the illumination pattern as desired.”)
As for Claim 3, which depends on Claim 1, Schmidt teaches wherein the photoreceptor unit is configured to perform pixel-by-pixel or region-by-region imaging simultaneously or sequentially (Fig. 2, Sensor 170, ¶50 L13-22).
As for Claim 4, which depends on Claim 1, Schmidt teaches wherein the photoreceptor unit is configured to acquire a first scene image corresponding to the first light pulse, a second scene image corresponding to the second light pulse, and a background scene image of the scene to be measured; and the processor unit is configured to acquire the scene distance information of the scene to be measured based on the background scene image, the first scene image and the second scene image (Fig. 7, ¶135 L14-23, ¶136, scene images captured by two FPAs 1219 and 1229 plus a third background scene captured by imaging subsystem 530 are used to calculate 3D distances of objects in the scenes.)
As for Claim 5, which depends on Claim 4, Schmidt teaches wherein the background scene image comprises a background scene image obtained by imaging the scene to be measured in a wavelength band not comprising a wavelength of the first light pulse nor a wavelength of the second light pulse, and/or a background scene image obtained by imaging the scene to be measured in a wavelength band comprising wavelengths of the first light pulse and the second light pulse while without the first light pulse and the second light pulse being emitted (¶s 93-94, the emitter can emit different wavelengths of light and the system can also capture and process reflections from ambient light sources.)
As for Claim 6, which depends on Claim 4, Schmidt teaches wherein the processor unit is configured to generate a target region image of corresponding to a target region comprising a plurality of sub-regions based on the first scene image, the second scene image and the background scene image, and the sub-regions comprise simple primitives and/or superpixel regions; and the processor unit is configured to generate scene distance information of the target region based on the first scene image, the second scene image and the target region image (See FIG. 6, illustrating the combining of the first and second pulse scenes [A] with the background scene image [B]).
As for Claim 11, which depends on Claim 6, Schmidt teaches further comprising a beam splitter unit (Fig. 6, beamsplitter 531, ¶95 L5-7), configured to guide the reflected light reflected by the object in the scene to be measured to the optical transmission unit, and to guide the reflected light reflected by the object in the scene to be measured to the photoreceptor unit, wherein the photoreceptor unit comprises at least a first photoreceptor sub-unit and a second photoreceptor sub-unit, the first photoreceptor sub-unit is configured to perform imaging on the reflected light, and the second photoreceptor sub-unit is configured to perform imaging on a reflected light of a natural light (Fig. 6, ¶95 L1-13); the first photoreceptor sub-unit is at least further configured to perform imaging with spatially uneven light pulses to generate an uneven light pulse scene image; and the scene distance information is generated based on the background scene image, at least the first scene image and the second scene image, the target region image, and/or the uneven light pulse scene image (Fig. 6, ¶95 L1-13).
As for Claim 13, which depends on Claim 1, Schmidt teaches wherein the optical transmission unit comprises a first optical transmission sub-unit and/or a second optical transmission sub-unit, and the photoreceptor unit comprises a first photoreceptor sub-unit and a second photoreceptor sub-unit; the three-dimensional distance measurement device further comprises a first beam splitter sub-unit and a second beam splitter sub-unit; the first optical transmission sub-unit, the first beam splitter sub-unit and the first photoreceptor sub-unit form a first sub optical path for imaging the light pulses (Fig. 6, ¶95 L1-13); the second optical transmission sub-unit, the second beam splitter sub-unit and the second photoreceptor sub-unit form a second sub optical path for imaging a visible light; the processor unit is configured to control alternate imaging or simultaneous imaging via the first sub optical path and/or the second sub optical path (Fig. 6, ¶95 L1-13); and the scene distance information is generated based on the background scene image, the first scene image and the second scene image, and the target region image (Fig. 6, ¶100 L1-23).
As for Claim 14, which depends on Claim 13, Schmidt teaches further comprising an amplifier unit, configured after the light source unit for amplifying the light pulses, or configured after the first optical transmission sub-unit or the first beam splitter sub-unit for amplifying the reflected light, wherein the processor unit is further configured to output the scene distance information and a scene image of the scene to be measured (Fig. 6, ¶95 L1-13), and the scene image comprises at least one of the group consisting of an image of geometric figures and an optical flow image (See FIG. 1, 102, showing Lidar imaging system capturing scene comprising two geometric objects.)
Claims 16 and 19-21 recite substantially the same subject matter as Claims 1 and 4-6, respectively, and stand rejected on the same basis accordingly.
Claim 17 recites substantially the same subject matter as Claims 2 and 3 combined and stands rejected on the same basis accordingly.
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Claims 7, 9-10, and 22-23 are rejected under 35 U.S.C. 103 as unpatentable over Schmidt and Amirsolaimani in view of Tay et al. (U.S. Pub. 20190311546)
As for Claim 7, which depends on Claim 6, Schmidt does not explicitly teach all the claim limitations.
But Tay teaches wherein the target region image is generated using a deep neural network; and the deep neural network is pre-optimized to perform sub-region segmentation based on the first scene image, the second scene image and the background scene image and generate the scene distance information based on the first scene image, the second scene image and the background scene image (¶59 L1-24).
It 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 to combine Schmidt and Amirsolaimani with Tay because using deep learning networks to analyze and recognize patterns in a 3D point cloud can aid an autonomous driving system to make faster better decisions.
As for Claim 9, which depends on Claim 7, Tay teaches wherein the deep neural network is updated in real time utilizing real-world scene images, further utilizing sub-region data with labels generated by a virtual three-dimensional world simulation corresponding to the real-world scene images, further utilizing a pre-labelled real-world image and corresponding sub-region label data, and/or further utilizing scene images and label data collected by at least one other three-dimensional distance measurement device (¶59 L1-24).
As for Claim 10, which depends on Claim 9, Tay teaches wherein an output of the deep neural network is calibrated with label data of a simulated virtual three-dimensional world as simple primitives and/or superpixel sub-regions comprising three-dimensional information, and the simple primitives and/or superpixel sub-regions are used to generate the scene distance information for the target region (¶59 L1-24).
Claims 22-23 recite substantially the same subject matter as Claims 7 and 9, respectively, and stand rejected on the same basis accordingly.
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Claim 12 is rejected under 35 U.S.C. 103 as unpatentable over Schmidt and Amirsolaimani in view of Happich (Julien Happich; "LCD-Controlled Headlights Turn Cars into Powerful Projectors"; Technology News, EENewsEurope.com website [full URL included in ref.]; 30 Jun 2017):
As for Claim 12, which depends on Claim 1, Schmidt does not explicitly teach all the claim limitations.
But Happich teaches wherein the three-dimensional distance measurement device is installed on a vehicle, and the light source unit is configured as a left headlight and/or a right headlight of the vehicle (P2/4: “A camera installed in the vehicle as well as a lidar sensor that measures optical distances and velocities forwards the environmental information to the headlight control unit via a computer which adjusts the individual image points of the display up to 60 times per second.” That is, the disclosed lidar system uses headlights for the light source.)
It 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 to combine Schmidt and Amirsolaimani with Happich because if headlights are present and already emitting light into the environment, it’s a simple and practical solution to use that light source in the lidar system.
Response to Arguments
Applicant's arguments filed 7 Nov 2025 that relate to newly amended claims and are not addressed in this section; the rejections above, however, address the latest version of the claims in detail. The Office has fully considered Applicant's arguments not related to the new amendments and finds them unpersuasive.
Applicant Argument:
Applicant argues (Remarks, P8/12) the following concerning the 112(a) rejections of Claim 7, 9-10, and 22-23:
Claims 7, 9-10 and 22-23 define the characteristics of "using a deep neural network" to generate the target region image. Applicant submits that it is well-known to one skilled in the art that the deep neural network is an existing technology.
For claim 6, superpixel technology is used to process the first scene image, the second scene image, and the background scene image to generate the target region image with superpixels/sub-regions as the unit. Among them, quantifying the original point cloud using superpixels is a technology for efficient image display, and it is not used in point cloud distance measurement technology; then, these three scene images with superpixels as the basic unit are used to calculate and obtain "distance information".
For claim 7, furthermore, using the neural network to generate three different target region images with superpixels/sub-regions as the basic unit, and further generating distance information based on this.
For claim 9, directly use the virtual 3D images processed with superpixels, blend them with real point cloud scene images, and combine the use of the first scene image, the second scene image, and the background scene image to generate distance information; this includes utilizing existing labels from the virtual world ( e.g. games). Thus, the specific inputs and outputs of the neural network, including training labels, as well as the special innovated distance generation method are all specified in detail in these claims. The description of the present application fully explains how to use the deep neural network to obtain the scene distance information. For example, as illustrate in paragraphs [0072]-[0073] and [0092]-[00110], the output of the deep neural network is calibrated with label data of a simulated virtual 3D world as simple primitives and/or superpixel sub-regions including 3D information, and the simple primitives and/or superpixel sub-regions are used to generate the scene distance information for the target region ...... in the whole process of processing, the deep neural network is updated in real time utilizing real-world scene images, further utilizing sub-region data with labels generated by a virtual three-dimensional world simulation corresponding to the real-world scene images, further utilizing a pre-labelled real-world image and corresponding sub-region label data, and/or further utilizing scene images and label data collected by at least one other three-dimensional distance measurement device.
Examiner Response:
The Office finds the arguments unpersuasive. That “it is well-known to one skilled in the art that the deep neural network is an existing technology” is not the issue. The issue is whether Applicant possessed a working deep neural network adapted to the claimed invention at the time of filing. The Spec. and claims describe a deep neural network in theoretical terms, a black-box high-level view of how one might adapt a deep neural net to the existing system, not in terms of an existing system that incorporates an existing sophisticated AI mechanism, which would reasonably convey to one skilled in the art that Applicant had possession of the claimed invention at the time of filing.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
Applicants should direct any inquiry concerning this or earlier communications to CLINT THATCHER at phone 571.270.3588. Examiner is normally available Mon-Fri, 9am to 5:30pm ET and generally keeps a daily 2:30pm timeslot open for interviews.
If attempts to reach the examiner by telephone are unsuccessful, Examiner’s supervisor, Yuqing Xiao, can be reached at (571) 270-3603.
Though not relied on, the Office considers the additional prior art listed in the Notice of Reference Cited form (PTO-892) pertinent to Applicant's disclosure.
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/Clint Thatcher/
Examiner, Art Unit 3645
/YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645
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