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 .
Specification
The disclosure is objected to because of the following informalities:
See [0025], reciting “A bounded grid grid”. Examiner suggests removing second instance of the word “grid” for clarity.
Appropriate correction is required.
Claim Objections
Claims 1 and 9 are objected to because of the following informalities:
Claim 1, Line 5: The term “objectID” (a single word) is used. Examiner finds this used in specification, Pg.11-12: “example of lidargraph file structure in JSON format”. Examiner suggests clarification, for example, using specification [0009]: “Objects - Each point has its own unique object identifier” or [0010]: “Attributes - Each object represented in a lidargraph has at a minimum its own object identifier”, to indicate the term “objectID” is a specific name/variable associated with coding and revising claim limitation to indicate the intension of the method step to assign an identifying feature to an object. For examination purposes, claim limitation will be interpreted as a generic variable name for a unique identifier for a point in a LIDAR frame.
Claim 1, Line 9, “objects position” and 11,”objects offset value; Examiner suggests the word “objects ” should be in possessive form, i.e., written as “object’s”. For examination purposes, the limitation will be interpreted in this manner.
Claim 9, Line 1, “the threshold is the centimeter level”; Examiner suggests for clarity, Applicant consider rephrasing to “the resolution threshold is centimeter level” to clarify meaning of the limitation and avoid reference to a specific term “the centimeter level”. For examination purposes, the meaning of Claim 9 limitation will be interpreted in this manner.
Appropriate correction is required.
Drawings
The drawings are objected to under 37 CFR 1.83(a) because Fig. 1 fails to show elements 4, 5 as described in the specification. Examiner suggests correction to other numerical annotations 1, 2, 3, 6, 7, 8, 9 depicted in gray on gray background field to provide improved legibility, as the numerals are only faintly discernable. Fig.1 is described in the specification, [0018]: “FIG. 1 is a view of a representative frame of lidar point cloud data showing the bounded grid with the positions of nine objects shown.” To understand the figure in view of information from specification, [0023]: “cuboids (the yellow rectangular 3d boxes) represent objects (vehicles, or pedestrians or buildings or any other object type)”, Examiner suggests replacing colors with symbols for clarity, since black and white/grayscale does not allow for a full understanding of what is being represented if Figure 1.
Likewise, Fig. 2, described in the specification in [0019]: “FIG. 2 is a simplified bounded grid with three example objects and an index showing the relative and absolute offset of each of the three objects” and [0035]: “Figure 2 shows the bounded grid from Figure 1, with three example objects located and the index of both relative offset and total or absolute offset for each object.” It is not clear what is depicted on the grid. The appears to have only three marks in the grid field as shown, and it is not clear whether the marks are letters, numbers, or symbols. The value of relative offset and total or absolute offset is not clear in what is presumed to be the legend on the right hand side of the grid. In addition, the label for the vertical axis is not understood (nor legible), and the horizontal axis is not labeled in the drawing, no explanation for meaning found in the specification.
Any structural detail that is essential for a proper understanding of the disclosed invention should be shown in the drawing. MPEP § 608.02(d). Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
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.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
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 of carrying out his invention.
Claims 2 and 5 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites the limitation "wherein the compressed position data for each object in each frame" in first line. There is insufficient antecedent basis for this limitation in the claim. Examiner notes reference in Claim 1, to which Claim 2 is dependent, of “lossless compression of a file of lidar point cloud data”, “tracking of each identified object's position in each frame”, “sequencing the position of each identified object in that frame”, “each identified objects position described as their integer offset” and “each identified objects offset value is stored in the compressed file”. The Examiner also notes Claim 1 recites “lidar data” (lines 1, 3, 4, 7) and “datatype” (line 13). However, the term “compressed position data” does not appear and is not defined in Claim 1, to which Claim 2 is dependent. Without specifying this term, it is not clear as to what is being “further compressed” as recited in Claim 2, leaving the linkage to Claim 1 limitations indefinite. For the purpose of the examination for differentiation over existing prior art, Examiner interprets the limitation “compressed position data” to mean a compressed lidar file of identified object offset data as recited in Claim 1.
Claim 5, dependent to Claim 1, recites “the zero based relative offset” in the second line. There is insufficient antecedent basis for this limitation in the claim. Examiner finds the term “zero based relative offset” is not defined or mentioned in Claim 1. Claim 1 recites terms “integer offset” and “objects offset value”, but does not determine a classification of offset, or a “zero” or “relative” offset. Examiner understands that Claim 5 does provide a mathematical equation for “zero based relative offset”. However, there is no linkage to Claim 1 to which Claim 5 depends. For the purpose of examination for differentiation over existing prior art, recited claim limitation, “the zero based relative offset” will be interpreted as “a zero based relative offset”, being defined initially with limitations of Claim 5.
Likewise, Claim 6, with dependence to Claim 5, recites “the zero based absolute offset”. There is insufficient antecedent basis for this limitation in the claim. Examiner find the term “zero based absolute offset” is not defined or mentioned in Claim 5. Examiner understands that Claim 6 does provide a definition for the term “zero based absolute offset”. However there is no linage to Claim 5 to which Claim 6 depends. For the purpose of examination for differentiation over existing prior art, recited claim limitation, “the zero based absolute offset” will be interpreted as “a zero based absolute offset”, being defined for the first time with limitations of Claim 6.
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, and 8 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over BEEK (US 10796457 B2) in view of SHULTS (US 20200164509 A1) and further in view of THAJEL (Thajel, et al., "A new technique for data compression", 2nd International Scientific Conference of Al-Ayen University, (ISCAU-2020) IOP Conf. Series: Materials Science and Engineering 928, 2020)
With respect to Claim 1, BEEK teaches:
A method of lossless compression of a file of lidar point cloud data
(For context, BEEK teaches using point cloud data in Abstract: “Methods and apparatus relating to image-based compression of Light Detection And Ranging (LIDAR) sensor data …ata stored in the one or more 2D arrays are compressed to generate a compressed version of the point cloud data”; BEEK teaches lossless compression method, COL5,L63,TableI: “Use Case I:…Compression requirements: Lossless or near-lossless”; Examiner notes BEEK is proper analogous art directed to same technical field as instant application.)
comprising the steps of: providing a file of lidar data,
(See, for example, COL2,L36: “represent the detected data as a point cloud data.”; and COL2,L59: “logic may be utilized to compress/decompress the LIDAR data”)
representing a predetermined number of frames of raw lidar data,
(BEEK See [0023]: “raw data can be obtained from the sensor(s) through an interface, and compression would be a processing step performed on the host computer/controller”; and [0029]: “FIGS. 1-2, operations for compression of lidar sensor data include: a) converting 204 raw distance data from the lidar sensor”; BEEK teaches receiving a number of files, [0030] In some embodiments, the operations for decompression include: a) receiving one or more bit streams (or compressed image files”
with a set of objects within the lidar data;
(BEEK teaches using LIDAR containing object information in COL4,L22: “LIDAR sensors typically measure ranges to objects in the environment by a process of scanning”)
for each frame of lidar point cloud data, sequencing the position of each identified object in that frame
(See Abstract: “compression of Light Detection And Ranging (LIDAR) sensor data with point re-ordering are described.”; and [0016]: “data pre-processing operation may be performed to re-order lidar data points based a given sensor scanning order and a given point scanning order used during encoding/compression.; process of scanning the environment results in a series of distance/range measurements in a particular order”; and [0063] Generally, image (and video) compression methods scan the data samples (pixels in the case of image data) in a particular order.”)
and based on each objects order of appearance in a bounded grid applied to each frame, reading from right to left, top to bottom,
(BEEK teaches this method in [0032]: “due to the specific structure of such lidar scans, it is relatively simple to pack the data in a 2-D grid or array.” and [0063]: “method is to scan the image row by row from top to bottom, and pixel by pixel from left to right. Another method may be to process the image block by block and scan the samples (pixels) within each block in a top-left to bottom-right or other order.”; and grid structure, in [0064]: “re-ordering of the data points can be implemented as a separate step or can be implemented as part of the process of packing the data into a 2-D image grid”)
However, BEEK is silent to the language of:
with a set of objects identified and classified within the lidar data;
assigning each identified object an objectId to allow tracking of each
identified object's position in each frame;
with each identified objects position described as their integer offset from the previous identified object in the bounded grid;
wherein each identified objects offset value is stored in the compressed file as a variable width integer datatype.
Nevertheless, SHULTS teaches:
with a set of objects identified and classified within the lidar data;
(SHULTS teaches identification of objects, see FIG.1 and [0070]: “compression engine 118 can also generate compositions that can include motion prediction cues…motion prediction cues can include, for an object identified within an image, an overlay vector indicating a predicted or projected path of the object”; .
assigning each identified object an objectId to allow tracking of each
identified object's position in each frame;
(SHULTS teaches sequential timed frames of data in [0060]: “data stream synchronization engine 110 cam match the time stamps of the data stream to the master clock and can interpolate or estimate the position of the data points between the neighboring time stamps.”; and object identification using tags, see FIG.1 and [0074]: “tagging engine 126 can apply tags to data streams or portions thereof based on the context of the autonomous system 106 during the recording of the data streams, based on events identified by the event detector 112, based on values of the data streams, or based on manual input from a user…tags can indicate times, events, objects within the data streams”; Examiner notes interpretation of claim limitation language, as discussed above, “objectID” to be analogous to reference use of the term “tags” to mean generally a label associated with a particular point or object in a frame of LIDAR data.)
However, BEEK, as modified by SHULTS, as taught above, is silent to the language of:
with each identified objects position described as their integer offset from the previous identified object in the bounded grid;
wherein each identified objects offset value is stored in the compressed file as a variable width integer datatype.
Nevertheless, THAJEL teaches:
with each identified objects position described as their integer offset from the previous identified object in the bounded grid;
(For context, Abstract: “proposed technique for document compression will be presented…proposed technique is a lossless”; THAJEL teaches offset in terms of a “delta” value, SS2.3: “Delta encoding represents streams of compressed pixels as the difference between the current value and the previous value [7].”; Examiner notes reference [7] in THAJEL is included as important art below, the developer of the delta technique for data compression; Examiner notes interpretation of claim limitation language “identified objects position” as analogous to cited reference, to mean generally a tag or designation of an identifiable point in an image that can be tracked, as is taught by reference using “pixels”. )
wherein each identified objects offset value is stored in the compressed file as a variable width integer datatype.
(THAJEL teaches this compression technique in general, see again SS2.3: “All the following pixels in the encoded file are equal to the difference between the corresponding value in the input data, and the previous value in the input data [8].”; Examiner notes interpretation as above, and citation in THAJEL to further explanation of data compression technique, including in important art of record below. Examiner points out that THAJEL is directed to the general “delta” method for monitoring change between subsequent files to produce compressed (reduced) data for storage.)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK to with a set of objects identified and classified within the lidar data; and to use the step of assigning each identified object an objectId to allow tracking of each identified object's position in each frame, such as that of SHULTS.
One of ordinary skill would be motivated to modify BEEK to with a set of objects identified and classified within the lidar data; and to use the step of assigning each identified object an objectId to allow tracking of each identified object's position in each frame, as taught by SHULTS because it would be an obvious improvement to ensure accurate object/point tracking frame to frame over time and allow for integrity in the final compressed file structure. Unique identifiers would be known by one of ordinary skill as a way to improve the overall management of large data sets.
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK, as modified by SHULTS, as taught above, to include with each identified objects position described as their integer offset from the previous identified object in the bounded grid; and the step of wherein each identified objects offset value is stored in the compressed file as a variable width integer datatype, such as that of THAJEL.
One of ordinary skill would be motivated to modify BEEK, as modified by SHULTS, as taught above, to include with each identified objects position described as their integer offset from the previous identified object in the bounded grid; and the step of wherein each identified objects offset value is stored in the compressed file as a variable width integer datatype, as taught by THAJEL because it would be an efficient way to decrease the overall size of a datafile. By using the delta (offset) method taught by THAJEL in combination with the data compression technique and process disclosed by BEEK, as modified by SHULTS, one of ordinary skill would understand how the size of the data file could be reduced and better managed, including accurate representation of raw data.
With respect to Claim 2, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 1
(See references as applied to Claim 1, above.)
SHULTS further teaches:
wherein the compressed position data for each object in each frame is further compressed using an additional lossless compression technique to result in the lidargraph compressed file.
(SHULTS teaches multiple compression steps, see, for example, COL2,L1: “data processing system can generate the third data stream based at least on the compressed portion of the first data stream that includes the event and the compressed portion of the second data stream that includes the event.”; Examiner notes interpretation of claim limitation language “object” to be analogous to reference teaching of “event”, generally to mean tracking of a pixel or point in a series of data frames. Examiner further notes references uses the term “stream” to mean a series of acquired data sets.)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to use the step of: wherein the compressed position data for each object in each frame is further compressed using an additional lossless compression technique to result in the lidargraph compressed file, such as that further disclosed by SHULTS.
One of ordinary skill would be motivated to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to use the step of: wherein the compressed position data for each object in each frame is further compressed using an additional lossless compression technique to result in the lidargraph compressed file, as is further taught by SHULTS because it would be understood as a way to further reduce large data sets, typical in the technical area of LIDAR point cloud data compression. One of ordinary skill would understand the advantage of a second compression process in the overall ability to manage large data sets over time, and find an obvious improvement in combination with the disclosure of BEEK, as modified by SHULTS and THAJEL in the ability to store and/or transmit the compressed file.
With respect to Claim 3, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 1
(See references as applied to Claim 1, above.)
BEEK further teaches:
wherein the position of each object is 2D, or (X, Y).
(See [0016]: “logic organizes and packs lidar sensor data into a two dimensional (2-D or 2D) image array and subsequently uses an image compression technique to compress the sensor data”)
With respect to Claim 4, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 1
(See references as applied to Claim 1, above.)
BEEK further teaches:
wherein the position of each object is 3D, or (X, Y, Z).
(BEEK teaches both 2D and 3D data representation, see for example, [0026]: “data generally refers to a set of points in a three dimensional (3D or 3-D) space, where each point is specified by its three dimensional X,Y,Z position/coordinates”)
With respect to Claim 8, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 1
(See references as applied to Claim 1, above.)
SHULTS further teaches:
where resolution reduction is utilized to remove data below a threshold level of resolution, the lidargraph file size can be further reduced.
(SHULTS teaches using data selected above a threshold, see COL1,L55: “data processing system can determine a network parameter of a network between the autonomous system and the remote data processing system. The data processing system can transmit the third data stream to the remote data processing system based on the network parameter being above a second threshold”)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to use the step of: where resolution reduction is utilized to remove data below a threshold level of resolution, the lidargraph file size can be further reduced, such as that further disclosed by SHULTS.
One of ordinary skill would be motivated to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to use the step of: where resolution reduction is utilized to remove data below a threshold level of resolution, the lidargraph file size can be further reduced, as is further taught by SHULTS because it would be understood that using resolution reduction based on a threshold value would provide valuable options for balancing data quality with practical operational needs based on system limitations, including storage, decompressions, and transmission of data. One of ordinary skill would see the logic of combining the threshold limit as taught by SHULTS with the method of BEEK, as modified by SHULTS and THAJEL to develop manageable sized file structures for compression processes.
Claim 7 rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over BEEK (US 10796457 B2) in view of SHULTS (US 20200164509 A1) and further in view of THAJEL (Thajel, et al., "A new technique for data compression", 2nd International Scientific Conference of Al-Ayen University, (ISCAU-2020) IOP Conf. Series: Materials Science and Engineering 928, 2020), as applied to Claim 1 above, and further in view of KOZAK (US 20140229453 A1).
With respect to Claim 7, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 1
(See references as applied to Claim 1, above.)
However, BEEK, as modified by SHULTS and THAJEL and as taught above, are silent to the language of:
wherein object indexing is utilized for the first 255 objects to further reduce the lidargraph file size.
Nevertheless, KOZAK teaches:
wherein object indexing is utilized for the first 255 objects to further reduce the lidargraph file size.
(For context, Abstract: “invention relates to a method and system for compressing and retrieving Light Detection and Ranging output data… losslessly compressing Light Detection and Ranging output data”; KOZAK teaches indexing, for example [0040]: “building specialized index subsets of the data” and a minimum number of classifications, see [0063]: “compression system described here allows each of the possible 255 point classifications”, and [0064]: “system further reduces the amount of data that needs to be decompressed for any one operation through the use of an index file for each cloud”)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to include wherein object indexing is utilized for the first 255 objects to further reduce the lidargraph file size, such as that of KOZAK.
One of ordinary skill would be motivated to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to include wherein object indexing is utilized for the first 255 objects to further reduce the lidargraph file size, as taught by KOZAK because it would be understood as an obvious way to improve a data compression method, since it represents a simple data representation, is a highly compact for of index encoding, and would allow an index value to be stored in a single byte. One of ordinary skill would see the advantage of the number 255, a single 8-bit byte (28-1), representing values from 0 to 255. This technique would minimize storage requirements for the index itself, and improve the method as taught by BEEK, modified by SHULTS and THAJEL, ultimately leading to improved compression by using a smaller more uniform index scheme, because index data with a smaller range and a higher probability of repeating patterns are more amendable for use in standard compression algorithms, for example, LZ77, which would be understood by one of ordinary skill in the art.
Claim 9 rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over BEEK (US 10796457 B2) in view of SHULTS (US 20200164509 A1) and further in view of THAJEL (Thajel, et al., "A new technique for data compression", 2nd International Scientific Conference of Al-Ayen University, (ISCAU-2020) IOP Conf. Series: Materials Science and Engineering 928, 2020), as applied to Claim 8 above, and further in view of CHEN (US 20180188042 A1).
With respect to Claim 9, BEEK, in view of SHULTS and further in view of THAJEL teaches:
The method of lossless compression of claim 8
(See references as applied to Claim 8, above.)
However, BEEK, as modified by SHULTS and THAJEL as taught above, is silent to the language of:
wherein the threshold is the centimeter level of resolution.
Nevertheless, CHEN teaches:
wherein the threshold is the centimeter level of resolution.
(For context, [0006]: “receive sensor data from vehicles travelling along routes within a geographical region and combine the data to generate a high definition map”, and [0019]:”FIG. 10 illustrates the process of LIDAR point cloud…vehicle computing system 120 use data compression techniques for being able to store and transfer map data thereby reducing storage and transmission costs”; Examiner finds the reference to be proper analogous art, as the subject matter is pertinent to the problem addressed in Applicant’s claimed invention.; CHEN teaches a grid related to data resolution, and centimeter level resolution, see [0082]: “occupancy map 530 comprises spatial 3-dimensional (3D) representation of the road and all physical objects around the road…data stored in an occupancy map 530 is also referred to herein as occupancy grid data…occupancy map 530 is represented as a 3D mesh geometry…In another embodiment, the occupancy map 530 is represented using a 3D volumetric grid of cells at 5-10 cm resolution”; Examiner notes interpretation of claim limitation language “centimeter level” to be analogous to reference term “5-10 cm”.)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to include wherein the threshold is the centimeter level of resolution, such as that of CHEN.
One of ordinary skill would be motivated invention to modify BEEK, as modified by SHULTS and THAJEL, as taught above, to include wherein the threshold is the centimeter level of resolution, as taught by CHEN because it would be understood that setting the threshold for data selection, as disclosed by SHULTS, to the level of centimeter resolution would be sufficient for preserving fine-grained details that may be necessary for accurate compression, while at the same time allowing for the rejection of less significant data in order to reduce file size. One of ordinary skill would understand that using a centimeter level resolution could allow a compression algorithm to either merge or discard points that are extremely close (less than a centimeter), which reduces the total number of points to consider with resulting in a noticeable loss of quality. One of ordinary skill would find the combination of the resolution suggested by CHEN to be an obvious improvement to the disclosed method of BEEK as modified by SHULTS and THAJEL.
Allowable Subject Matter
Claims 5 and 6 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.
The following is a statement of reasons for the indication of allowable subject matter:
With respect to Claim 5, examiner notes the equation recited for zero based relative offset would be well known to one of ordinary skill in the art as the difference between the row-major address (sometimes known as “index”) of an element [x1, y1] and [x2, y2] in a 2D array. Specifically, the Claim 5 recited a mathematical offset for an array with 20 rows, with the term “zero based” referring to the initial element in both row and column being zero. While Examiner finds the general equation for the zero based offset based on row-major consideration is ubiquitously available as a curricular component for many introductory level data structure/computer science courses, online videos, and tutorials aimed at teaching row-major indexing for array elements to reduce the two component “name” to a single, unique value. However, a specific reference for a 20 row, 2D array in the same or a similar technical area was not found. Examiner found no single reference, or a combination of references provided a hint or suggestion for reasonable success using the specific equation for a zero based offset for a 2D array with 20 rows as claimed by Applicant and recited in Claim 5. Claim 6 incorporates the limitations of Claim 5, and as such constitutes allowable subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Foreign Patent Literature
LI (WO 2023045044 A1) – teaches point cloud coding method and apparatus, image layer division, lossless compression.
Non-Patent Literature
ISENBURG (Martin Isenburg, “LASzip: Lossless Compression of Lidar Data”, Photogrammetric Engineering & Remote Sensing Vol. 79, No. 2, February 2013, pp. 209–217).
KIM (Kim, et al., “LiDAR Point Cloud Compression by Vertically Placed Objects Based on Global Motion Prediction”, IEEE Access, 2022)
DIPPERSTEIN, “Adaptive Delta Coding Discussion and Implementation”, online paper, cited by THAJEL, 2018)
SMITH (“The Scientist and Engineer's Guide to Digital Signal Processing”, Second Edition, copyright © 1997-1999 by California Technical Publishing)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TONI D SAUNCY whose telephone number is (703)756-4589. The examiner can normally be reached Monday - Friday 8:30 a.m. - 5:30 p.m. ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lisa Caputo can be reached at (571) 272-2388. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TONI D SAUNCY/Examiner, Art Unit 2863
/LISA M CAPUTO/Supervisory Patent Examiner, Art Unit 2863