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 .
Response to Arguments
Applicant's arguments filed 05/14/2025 have been fully considered but they are not persuasive. See mapping and rejection bellow.
Applicant’s arguments with respect to claim(s) bellow have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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) 1, 8, 15, 16 and claims bellow are rejected under 35 U.S.C. 103 as being unpatentable over D1 US 5379044 A.
Regarding claims 1, 8 D1 teaches
a memory configured to store a plurality of track information generated in a previous step; and
a controller electrically connected to the memory, wherein the controller is configured to(implicit)
generating a plurality of predicted tracks from a plurality of track information generated in a previous step;(claim 1 col 3 lines 8-13)
generating a relationship data set for each predicted track(col 3 lines 42-55 clusters , col 3 lines 42-55 col 12 lines 25-34 According to col 3 tracks have been separated into clusters which are considered boxes then for each box hypotheses are formed which sais that relationship between hypothesis and boxes/clusters are formed. If hypothesis belong to cluster then it is at least Boolean operator “yes” if no then “No”) and the plurality of predicted tracks
the relationship data set including link relationships between a corresponding predicted track and object boxes associated with the corresponding predicted track and link information of the object boxes to other predicted tracks, wherein each box is defined as a shape representation encompassing LiDAR points clustered for each object
determining one of two or more predicted tracks for an object box which has link relationships with the two or more predicted tracks, based on association scores between the two or more predicted tracks and the object box(col 3 liens 23-33)
wherein the link relationships(col 3 line 67-col 4 line 6 “score function”) include a link relationship of a predicted track(likelihood of association of the observation to a track ), which is associated with multiple obiect boxes(observation), with the multiple object boxes;
Regarding claims although D1 does not explicitly teach lidar and vehicle lidar is one of the specific types of radar which in the past was called laser radar and therefore using lidar is just one particular very well known to the art devices and placing radar or lidar on vehicle is also very well known and practices in order to measure the distance to different objects(or in military to the flying objects).
It is important to note that hypothesis in art D1 are generated after clustering of the initial data, but nothing in the claim requires generation of the tracks prior to object box generation. The only requirement is that link between the predicted tracks and clusters is established.
Claim(s) 1, 8, 15, 16 and claims bellow are rejected under 35 U.S.C. 103 as being unpatentable over D0 US 20120093359 A1.
1. (Currently Amended) A method for tracking objects, the method comprising:
generating a plurality of predicted tracks from a plurality of track information generated in a previous step;[0047-0049] (fig. 3,5 fitted curves represent predicted tracks )
generating a relationship data set for each predicted track based on associations between the plurality of object boxes and the plurality of predicted tracks,
the relationship data set including link relationships between a corresponding predicted track and object boxes associated with the corresponding predicted track and link information of the object boxes to other predicted tracks,[0050] (associating the track with clusters)
wherein each box is defined as a shape representation encompassing clustered for each object; and[0043, 0050] (box is implicit )
determining one of two or more predicted tracks for an object box which has link relationships with the two or more predicted tracks, based on association scores between the two or more predicted tracks and anthe object box ; and associating the determined one of the two or more predicted tracks with a track of the object box having the link relationships.[0050 -0053]
Regarding claims although D0 does not explicitly teach lidar and vehicle lidar is one of the specific types of radar which in the past was called laser radar and therefore using lidar is just one particular very well known to the art devices and placing radar or lidar on vehicle is also very well known and practices in order to measure the distance to different objects(or in military to the flying objects).
2,9, 16 The method according to claim 1, wherein the link relationships are generated by recording an object box having the associations with each of the plurality of predicted tracks as an association candidate, and recording information of a second predicted track having the associations with the association candidate. D1 (col 3 liens 23-33)/ D0[0050-0053]
6, 13, 19(Currently Amended) The method according to claim 1, wherein the association scores are determined based on a distance between a tracking point of each of the plurality of predicted tracks and a tracking point of each of the object boxes having the link relationships with the two or more predicted tracks, a proportion of a region in which each of the plurality of predicted tracks and each of the object boxes having the link relationships with the two or more predicted tracks, reliability of each of the plurality of predicted tracks, or an age of each of the plurality of predicted tracks. (Obvious over D0[0050-0053])
7, 14 , 20(Previously Presented) The method according to claim 6, wherein the association scores are determined further based a comparison between on a horizontal or vertical length of a box representing each of the plurality of predicted tracks and a horizontal or vertical length of each of the object boxes having the link relationships with the two or more predicted tracks, depending on position information of each of the plurality of predicted tracks in the previous step and position information of each of the plurality of predicted tracks in the current step. (Obvious over D0[0050-0053][0033])
Although does not explicitly say horizontal or vertical length of a box representing each of the plurality of predicted tracks D0 teaches obtaining clusters from common object and therefore restricting horizontal and vertical length is obvious cuts on the shape of the common object.
Allowable Subject Matter
Claims 3, 4, 10, 11, 17, 18 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/HOVHANNES BAGHDASARYAN/Examiner, Art Unit 3645
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