DETAILED ACTION
Applicant presents Claims 1-19 for examination. The Office rejects Claims 1-19 as detailed below.
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 1-19 are rejected under 35 U.S.C. 103 as being unpatentable over
Hitomi – U.S. Pub. 20190227174 – in view of IDS entry Tubert et al. – U.S. Pub. 20210183018 +_+_+
As for Claim 1, Hitomi teaches a time-of-flight detection circuitry (¶32|1: “A TOF camera operates by providing pulsed or modulated illumination 105 and then detecting the reflected
light 110 from a scene or object 115. A depth separation between the sensor and the object 115 can be detected by observing a phase shift between the illumination 105 and the reflection 110.”) configured to determine a single-frame noise estimate based on a common mode estimator (¶85|1: “So, the next part of the process is to obtain an estimate [<single-frame] of [common mode>] cmactive·”) and a dark frame measurement (¶34|1: “As discussed in more detail below, a subset 130 of one or more of the pixels (for example one or two lines of pixels in the array) is blanked from incident light. This way, the subset 130 can be used to detect a so-called dark offset [dark frame measurement], or in other words an output from the image capture sensor which is entirely independent of the reflected light 110 and also any ambient light incident upon the pixel array.”) Hitomi teaches gathering noise info including ambient (external) and dark frame (internal), but does not explicitly teach filtering depth data based on the noise information.
But Tubert teaches to perform filtering of depth data based on the single-frame noise estimate (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
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 Hitomi with Tubert because filtering both external and internal noise from the signal results in a higher signal to noise ratio and improved measurement accuracy.
As for Claim 2, which depends on Claim 1, Tubert teaches further configured to determine a total signal of a frame based on the common mode estimator of a frame and the dark frame measurement, and to determine the single-frame noise estimate based on the total signal of the frame (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 3, which depends on Claim 1, Tubert teaches wherein the single-frame noise estimate is represented by a single-frame signal-to-noise ratio, by a depth noise standard deviation, or by a phasor variance (¶10|1: “In some embodiments, the signal-to-noise ratio is determined on the basis of the amplitude of the signal, of an ambient value and of a predetermined standard deviation.”)
As for Claim 4, which depends on Claim 1, Tubert teaches wherein the depth data is obtained from sensor raw data (¶6|1: “Some embodiments relate to the filtering of [raw] data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 5, which depends on Claim 1, Tubert teaches wherein the filtering of the depth data comprises direct-global separation filtering (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels [i.e., direct-global separation filtering].” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 6, which depends on Claim 5, Tubert teaches wherein direct-global separation filtering comprises filtering of the depth data based on the single-frame noise estimate (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels [i.e., direct-global separation filtering].” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 7, which depends on Claim 5, Tubert teaches wherein the direct-global separation filtering comprises determining an accuracy (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels [i.e., direct-global separation filtering].” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 8, which depends on Claim 7, Tubert teaches wherein the accuracy is determined based on a trueness value and based on the depth noise standard deviation (¶10|1: “In some embodiments, the signal-to-noise ratio is determined on the basis of the amplitude of the signal, of an ambient value and of a predetermined standard deviation.”)
As for Claim 9, which depends on Claim 8, Tubert teaches wherein direct-global separation filtering is carried out based on a comparison of the accuracy without direct-global separation with the accuracy with direct-global separation (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels [i.e., direct-global separation filtering].” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 10, which depends on Claim 1, Tubert teaches wherein the filtering of the depth data comprises precision filtering (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 11, which depends on Claim 10, Hitomi teaches wherein the precision filtering comprises filtering of the depth data based on the single-frame noise estimate (¶85|1: “So, the next part of the process is to obtain an estimate [<single-frame] of [common mode>] cmactive·”)
As for Claim 12, which depends on Claim 10, Tubert teaches wherein the precision filter is applied based on a precision estimate (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 13, which depends on Claim 12, Tubert teaches wherein the precision estimate is based on a relation between the depth noise standard deviation and the depth data (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 14, which depends on Claim 12, Tubert teaches wherein the precision filtering comprises invalidating depth data based on the precision estimate (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 15, which depends on Claim 1, Tubert teaches wherein the filtering of the depth data comprises noise-modelled bilateral filtering (¶62|1: “The weighting coefficients are determined on the basis of the signal-to-noise ratio SNR31 of the data signal from the pixel 31 and of the data signals from the pixels neighboring the pixel 31 and on the basis of the data coefficients calculated on the basis of the data DATA31 from pixel 31 and of the data from the pixels neighboring the pixel 31 (for example bilateral filtering).”)
As for Claim 16, which depends on Claim 15, Tubert teaches wherein the noise-modelled bilateral filtering comprises determining a denoised depth value based on a similarity (¶62|1: “The weighting coefficients are determined on the basis of the signal-to-noise ratio SNR31 of the data signal from the pixel 31 and of the data signals from the pixels neighboring the pixel 31 and on the basis of the data coefficients calculated on the basis of the data DATA31 from pixel 31 and of the data from the pixels neighboring the pixel 31 (for example bilateral filtering).”)
As for Claim 17, which depends on Claim 16, Tubert teaches wherein the similarity is determined based on a weighted average of neighboring pixels in a predetermined radius (¶6|1: “Some embodiments relate to the filtering of data signals transmitted by pixels, and more particularly pixels of time-of-flight sensors that measure three-dimensional scenes. Some embodiments configure a filtering device for filtering data signals generated by a pixel in an array of pixels according to the position of the pixel in the array and according to the signal-to-noise ratio of a plurality of pixels.” Further, (¶14|1) “[i]n some embodiments, the extent of the pixels neighboring the pixel is determined on the basis of the signal-to-noise ratio of the data signal from the pixel.”)
As for Claim 18, which depends on Claim 16, Hitomi teaches wherein the similarity is determined based on the single-frame noise estimate (¶85|1: “So, the next part of the process is to obtain an estimate [<single-frame] of [common mode>] cmactive·”)
Claim 19 recites substantially the same subject matter as Claim 1 and stands rejected on the same basis accordingly.
Conclusion
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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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