UNITED STATES PATENT AND TRADEMARK OFFICE
`
`__________________
`
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`__________________________________________________________________
`
`TOYOTA MOTOR CORPORATION
`Petitioner
`
`Patent No. 5,845,000
`Issue Date: December 1, 1998
`
`Title: OPTICAL IDENTIFICATION AND MONITORING SYSTEM USING
`PATTERN RECOGNITION FOR USE WITH VEHICLES
`__________________________________________________________________
`
`PETITION FOR INTER PARTES REVIEW
`OF U.S. PATENT NO. 5,845,000
`PURSUANT TO 35 U.S.C. § 312 and 37 C.F.R. § 42.104
`
`Case No. IPR2015-00262
`________________________________________________________________
`
`

`

`
`TABLE OF CONTENTS
`
`I.
`
`MANDATORY NOTICES (37 C.F.R. § 42.8) ......................................................... 1
`A.
`Real Party-in-Interest (37 C.F.R. § 42.8(b)(1)) ................................................ 1
`B.
`Related Matters (37 C.F.R. § 42.8(b)(2)) ......................................................... 1
`C.
`Counsel & Service Information (37 C.F.R. §§ 42.8(b)(3)-(4)) ...................... 2
`PAYMENT OF FEES (37 C.F.R. § 42.103) ............................................................. 3
`II.
`III. REQUIREMENTS FOR IPR (37 C.F.R. § 42.104) ................................................. 3
`A. Grounds for standing (37 C.F.R § 42.104(a)) ................................................. 3
`B.
`Identification of Challenge (37 C.F.R. § 42.104(b)) and Relief
`Requested (37 C.F.R. § 42.22(a)(1)) ................................................................. 4
`Claim Construction (37 C.F.R. § 42.104(b)(3)) .............................................. 6
`C.
`IV. OVERVIEW OF THE ’000 PATENT ..................................................................... 8
`V. HOW CHALLENGED CLAIMS ARE UNPATENTABLE (37 C.F.R. §§
`42.104(B)(4)-(5)) ............................................................................................................ 9
`A. Ground 1: Claims 10, 11, 19 and 23 Are Obvious Under 35 U.S.C.
`§ 103(a) over Lemelson ..................................................................................... 9
`B. Ground 2: Claims 10, 11, 19 and 23 Are Obvious Under 35 U.S.C. §
`103(a) over Lemelson in View of Nishio ...................................................... 22
`C. Ground 3: Claims 10, 11, 19 and 23 Are Obvious Under 35 U.S.C. §
`103(a) over Lemelson in View of Asayama .................................................. 24
`D. Ground 4: Claims 16, 17, and 20 Are Obvious Under 35 U.S.C. §
`103(a) over Lemelson in View of Yanagawa ................................................ 25
`VI. CONCLUSION .......................................................................................................... 27
`
`
`
`i
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`
`Exhibit 1101
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`Exhibit 1102
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`Exhibit 1103
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`Exhibit 1104
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`Exhibit 1105
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`Exhibit 1106
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`Exhibit 1107
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`Exhibit 1108
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`LISTING OF EXHIBITS
`
`U.S. Patent No. 5,845,000 to Breed et al.
`
`U.S. Patent No. 6,553,130 to Lemelson et al.
`
`File History for U.S. Patent Application No. 08/105,304
`
`U.S. Patent No. 5,541,590 to Nishio
`
`File History for US Patent Application No. 08/097,178
`
`U.S. Patent No. 5,214,408 to Asayama
`
`Japanese Unexamined Patent Application Publication JP-
`S62-131837 to Yanagawa
`
`English Translation of Japanese Unexamined Patent
`Application Publication JP-S62-131837 to Yanagawa
`
`Exhibit 1109
`
`Declaration of Nikolaos Papanikolopoulos, Ph. D.
`
`
`
`ii
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`

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`Pursuant to 35 U.S.C. §§ 311-319 and 37 C.F.R. Part 42, real party in interest
`
`Toyota Motor Corporation (“Toyota” or “Petitioner”) respectfully requests inter partes
`
`review of claims 10, 11, 16, 17, 19, 20, and 23 of U.S. Patent No. 5,845,000 (“the ’000
`
`patent”), filed June 7, 1995 and issued December 1, 1998 to David S. BREED.
`
`According to U.S. Patent and Trademark Office records, the ’000 patent is currently
`
`assigned to American Vehicular Sciences LLC (“AVS” or the “Patent Owner”).
`
`This Petition for Inter Partes Review is being filed along with a motion requesting
`
`joinder with the pending inter partes review initiated by Mercedes-Benz USA LLC
`
`(“Mercedes”) concerning the ’000 patent: Mercedes-Benz USA LLC, v. American Vehicular
`
`Sciences, LLC, Case No. IPR2014-00647 (“Mercedes 647 IPR”). This Petition proposes
`
`a subset of the same grounds on which the Board instituted inter partes review of claims
`
`10, 11, 15, 16, 17, 19, 20, and 23 in the Mercedes 647 IPR.1 (IPR2014-00647 Institution
`
`Decision, at 29.)
`
`I. MANDATORY NOTICES (37 C.F.R. § 42.8)
`A. Real Party-in-Interest (37 C.F.R. § 42.8(b)(1))
`Petitioner, Toyota, is the real party-in-interest.
`
`B. Related Matters (37 C.F.R. § 42.8(b)(2))
`The ’000 patent is currently the subject of the following litigation: American
`
`Vehicular Sciences LLC v. Toyota Motor Corp. et al., No. 2:14-cv-13017 (E.D. Mich.), which
`
`was transferred from the Eastern District of Texas, No. 6:12-CV-406 (E.D. Tex.)
`
`Toyota does not seek inter partes review of claim 15.
`1
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`
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`1
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`

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`(collectively, the “AVS 406 Litigation”); Petitioner is a named defendant in the AVS
`
`406 Litigation. The earliest that Petitioner or any of its subsidiaries was served with the
`
`complaint was July 26, 2012. Petitioner previously filed a petition for inter partes review
`
`in IPR 2013-00424 on July 12, 2013 asserting invalidity of claims 10, 11, 16, 17, 19, 20,
`
`and 23 of the ’000 patent. On January 14, 2014 (Paper 16), the Board instituted the
`
`proceeding with respect to all challenged claims (the “Toyota IPR”). That proceeding
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`is currently pending.
`
`Petitioner has also filed petitions in IPR2013-00419, -00420, -00421, -00422 and
`
`-00423, which addressed patents that were asserted against Toyota in a related case:
`
`American Vehicular Sciences LLC v. Toyota Motor Corp., et al., 12-CV-410 (E.D. Tex.)
`
`(“AVS 410 Litigation”). IPR2013-00420, -00422, and -00423 have settled and been
`
`terminated, and the Board has issued a final written decision in IPR2013-00421.
`
`IPR2013-00419, which addresses U.S. Patent No. 6,772,057 (“the ’057 patent”), is
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`currently pending. Petitioner is concurrently filing a motion for joinder in IPR2014-
`
`00646, which also addresses the ’057 patent. On November 13, 2014, Petitioner filed a
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`request for ex parte reexamination of claims 10, 11, 16, 17, 19, 20 and 23 of the ’000
`
`patent. Petitioner is not aware of any other pending judicial or administrative matter
`
`that would affect, or be affected by, a decision in this proceeding.
`
`C. Counsel & Service Information (37 C.F.R. §§ 42.8(b)(3)-(4))
`Lead Counsel: Matt Berkowitz (Reg. No. 57,215)
`
`Back-up Counsel: Thomas R. Makin (pro hac vice to be requested upon authorization)
`
`
`
`2
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`

`

`Petitioner requests authorization to file a motion for Thomas R. Makin to appear pro
`
`hac vice as backup counsel. Mr. Makin is an experienced litigation attorney in patent
`
`cases, admitted to practice law in New York, and in several United States District
`
`Courts and Courts of Appeal. Mr. Makin has an established familiarity with the subject
`
`matter at issue and represents Petitioner as a defendant in the related AVS 406
`
`Litigation, identified above. Additionally, Mr. Makin was previously admitted pro hac
`
`vice as backup counsel in IPR2013-00424 regarding the ’000 patent.
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`Electronic Service Information: ptab@kenyon.com and mberkowitz@kenyon.com
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`Post and Delivery: Kenyon & Kenyon LLP, One Broadway, New York, NY 10004
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`Telephone: 212-425-7200
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`Facsimile: 212-425-5288
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`II.
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`PAYMENT OF FEES (37 C.F.R. § 42.103)
`The USPTO is authorized to charge all fees required in connection with this
`
`Petition, as well as any other fees that may be required connection with this Petition or
`
`these proceedings, to the deposit account of Kenyon & Kenyon LLP, Deposit
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`Account 11-0600.
`
`III. REQUIREMENTS FOR IPR (37 C.F.R. § 42.104)
`A. Grounds for standing (37 C.F.R § 42.104(a))
`Petitioner certifies that the ’000 patent (Ex. 1101) is available for inter partes
`
`review and that Petitioner is not barred or estopped from requesting an inter partes
`
`review challenging the patent’s claims on the grounds identified in this Petition.
`
`
`
`3
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`

`

`B.
`
`Identification of Challenge (37 C.F.R. § 42.104(b)) and Relief
`Requested (37 C.F.R. § 42.22(a)(1))
`Petitioner respectfully requests that inter partes review be instituted and claims 10,
`
`11, 16, 17, 19, 20, and 23 of the ’000 on the grounds set forth below. Cancellation of
`
`these claims is requested.
`
`The ’000 patent (Ex. 1101) was filed as U.S. Patent App. No. 08/474,786 on
`
`June 7, 1995 and is identified as a continuation-in-part of a chain of applications, the
`
`earliest of which is U.S. Patent App. No. 878,571, which was filed on May 5, 1992 and
`
`is abandoned. The ’000 patent is also identified as a continuation-in-part of U.S. Patent
`
`App. No. 08/247,760 filed on May 23, 1994. In the AVS 406 litigation, AVS
`
`contended that the earliest priority date available for claims 10, 11, 19, and 23 is May
`
`23, 1994, and that the earliest priority date available for claims 16, 17, and 20 is June 7,
`
`1995. Accordingly, Petitioner contends that claims 10, 11, 19, and 23 are not entitled
`
`to a priority date earlier than May 23, 1994, and that claims 16, 17, and 20 are not
`
`entitled to a priority date earlier than June 7, 1995. In IPR2013-00424, AVS did not
`
`assert that it was entitled to any earlier priority date.
`
`Petitioner relies on the following patents and publications. None of them were
`
`of record during prosecution of the ’000 patent.
`
`1) U.S. Patent No. 6,553,130 (“Lemelson,” Ex. 1102) issued on April 22, 2003
`
`from U.S. Appl. No. 08/671,853 (“’853 app.”), filed on June 28, 1996. The ’853
`
`application is a continuation of U.S. Appl. No. 08/105,304 (“’304 app.,” Ex. 1103),
`
`which was filed on August 11, 1993. As indicated where applicable throughout this
`4
`
`
`

`

`petition, the originally filed specification of the ’304 app. contains the same relevant
`
`disclosure as that of Lemelson. Therefore, Lemelson qualifies as prior art against the
`
`’000 patent under 35 U.S.C. § 102(e) for claims 10, 11, 16, 17, 19, 20, and 23.
`
`2) U.S. Patent No. 5,541,590 to Nishio (“Nishio,” Ex. 1104) issued on July 30,
`
`1996 from U.S. Appl. No. 375,249 (“’249 app.”), filed on Jan. 19, 1995. The ’249
`
`application is a continuation of U.S. Appl. No. 08/097,178 (“’178 app,” Ex. 1105),
`
`which was filed on July 27, 1993. As indicated where applicable through this petition,
`
`the originally filed specification of the ’178 app. contains the same relevant disclosure
`
`as that of Nishio. Therefore, Nishio qualifies as prior art against the ’000 patent under
`
`35 U.S.C. § 102(e) for claims 10, 11, 16, 17, 20 and 23.
`
`3) U.S. Patent No. 5,214,408 to Asayama (“Asayama,” Ex. 1106) was filed on
`
`Oct. 24, 1991, and issued on May 25, 1993. It qualifies as prior art against the ’000
`
`patent under at least 35 U.S.C. § 102(e) for claims 10, 11, 19 and 23, and under 35
`
`U.S.C. § 102(b) for claims 16, 17, and 20.
`
`4) Japanese Unexamined Patent Application Publication No. S62-131837 to
`
`Yanagawa (“Yanagawa,” Ex. 1107) published June 15, 1987, and qualifies as prior art
`
`against the ’000 patent under 35 U.S.C. § 102(b). Yanagawa was published in Japanese.
`
`Pursuant to 37 C.F.R. § 42.63(b), an English translation and associated affidavits
`
`accompany this Petition as Ex. 1108.
`
`Petitioner requests that claims 10, 11, 16, 17, 19, 20 and 23 be cancelled on the
`
`following grounds:
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`
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`5
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`

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`Ground 1: Claims 10, 11, 19 and 23 are Obvious Under 35 U.S.C. § 103(a) in
`
`View of Lemelson.
`
`Ground 2: Claims 10, 11, 19 and 23 are Obvious Under 35 U.S.C. § 103(a)
`
`Over Lemelson in View of Nishio.
`
`Ground 3: Claims 10, 11, 19 and 23 are Obvious Under 35 U.S.C. § 103(a)
`
`Over Lemelson in View of Asayama.
`
`Ground 4: Claims 16, 17, and 20 are Obvious Under 35 U.S.C. § 103(a) over
`
`Lemelson in View of Yanagawa.
`
`The above-listed grounds of unpatentability are explained in detail in Section V,
`
`below. For support, petitioners rely on the Declaration of Nikolaos Papanikolopoulos,
`
`Ph.D., which is attached hereto as Ex. 1109.
`
`C. Claim Construction (37 C.F.R. § 42.104(b)(3))
`For purposes of this IPR only, Petitioner proposes the construction of the claim
`
`terms as set forth by the Board in its institution decisions in IPR2013-00424, pp. 9-26,
`
`and IPR2014-00647, pp. 9-12. Those constructions are as follows:
`
`Claim Term
`“pattern recognition
`
`Board’s Construction
`“an algorithm which processes a signal that is generated
`
`algorithm” (claims 10 and
`
`by an object, or is modified by interacting with an
`
`16)
`
`
`
`object, for determining to which one of a set of classes
`
`the object belongs” (Toyota IPR at 10-11.)
`
`6
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`

`

`“trained pattern recognition
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`“a neural computer or microprocessor trained for
`
`means for…” (10, 16)
`
`pattern recognition, and equivalents thereof” (Toyota
`
`IPR at 12-16.)
`
`“identify” (10, 16, 23)
`
`“determining that the object belongs to a particular set
`
`or class” (Toyota IPR at 16.)
`
`“transmitter means for
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`“infrared, radar, and pulsed GaAs laser systems” and
`
`transmitting…” (10)
`
`“transmitters which emit visible light” (Toyota IPR at
`
`16-19.)
`
`“reception means for
`
`“a CCD array and CCD transducer” (Toyota IPR at 19-
`
`receiving…” (10, 16)
`
`20.)
`
`“processor means…for
`
`For this petition, a processor provides sufficient
`
`processing…” (10, 16)
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`structure to perform the function. (Toyota IPR at 19-
`
`21.)
`
`“categorization means…
`
`“a neural computer, a microprocessor, and their
`
`for categorizing…” (10, 16)
`
`equivalents” (Toyota IPR at 21-22.)
`
`“output means…” (10, 16)
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`“electronic circuit or circuits capable of outputting a
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`signal to another vehicle system” (Toyota IPR at 22-24.)
`
`“dimming the headlights”
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`“decreasing the intensity or output of the headlight to a
`
`(16)
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`lower level of illumination” (Toyota IPR at 25.)
`
`“measurement means for
`
`The recited “radar” provides sufficient structure to
`
`
`
`7
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`

`

`measuring…” (11)
`
`perform the recited functions. (Toyota IPR at 24.)
`
`“wherein said categories
`
`“categorizing radiation from taillights of a vehicle-in-
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`further comprise radiation
`
`front, which may include additional types of radiation”
`
`from taillights of a vehicle-
`
`(Toyota IPR at 25-26.)
`
`in-front” (17)
`
`“generated a pattern
`
`Requires training using patterns of waves actually
`
`recognition algorithm from
`
`received from possible exterior objects. (Mercedes 647
`
`data of possible exterior
`
`IPR at 12.)
`
`objects and patterns of
`
`received electromagnetic
`
`illumination from the
`
`possible exterior objects”
`
`
`IV. OVERVIEW OF THE ’000 PATENT
`The ’000 patent is generally directed to monitoring the exterior and interior of a
`
`vehicle and affecting a vehicle subsystem in response to the identification of an object.
`
`(Ex. 1101, Abstract.) The claims at issue in this Petition relate only to exterior
`
`monitoring. Objects are illuminated with electromagnetic radiation, and a lens is used
`
`to focus the illuminated images onto the arrays of a charge coupled device (CCD).
`
`(Ex. 1101, Abstract, 7:26-40.) Computational means using trained pattern recognition
`
`analyzes the signals received at the CCD to identify external objects, which, in turn, are
`
`used to affect the operation of other vehicular systems. (Id. at Abstract.) The ’000
`8
`
`
`

`

`patent discloses that a vehicle computation system uses a “trainable or a trained pattern
`
`recognition system,” which relies on pattern recognition to process signals and to
`
`“identify” an object exterior to the vehicle. (Id. at col. 3:21-44.) Figures 7 and 7A
`
`illustrate portions of the sensor system that use transmitters, receivers, circuitry, and
`
`processors to perform pattern recognition of external objects.
`
`The ’000 patent also discloses a system for detecting the headlights or taillights
`
`of other vehicles and dimming the vehicle’s headlights in response. (Ex. 1101, col.
`
`9:54-58.) A CCD array is designed to be sensitive to visible light and does not use a
`
`separate source of illumination. (Id. at col. 19:28-31.) In another embodiment, external
`
`objects are illuminated with “electromagnetic, and specifically infrared, radiation,” and
`
`lenses are used to focus images onto one or more CCDs arrays. (Id. at Abstract, 7:26-
`
`35.)
`
`V. HOW CHALLENGED CLAIMS ARE UNPATENTABLE (37 C.F.R. §§
`42.104(B)(4)-(5))
`A. Ground 1: Claims 10, 11, 19 and 23 Are Obvious Under 35 U.S.C.
`§ 103(a) over Lemelson
`
`Claims 10, 11, 19 and 23 are obvious under 35 U.S.C. § 103(a) over Lemelson.
`
`This ground was already presented in the Mercedes 647 IPR and instituted by the
`
`Board.
`
`Lemelson teaches an exterior monitoring system that one of ordinary skill could
`
`implement to identify objects outside of a moving vehicle and affecting a vehicle
`
`subsystem in response to that identification. (Ex. 1102, Abstract, 2:14-23, 2:53-3:39,
`
`
`
`9
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`

`

`5:15-18, Fig. 1; Ex. 1103, Abstract; pp. 7-10, 12, Fig. 1.) For example, Figure 1 of
`
`Lemelson discloses many aspects of the challenged claims, including a radar/lidar
`
`computer 14 for locating an exterior object based on received radar or lidar signals that
`
`includes both electromagnetic radiation emitters and receivers, a camera receiver 16 to
`
`receive waves emitted from or reflected by objects in the exterior environment, a
`
`processor 19 for classifying and identifying exterior objects, and vehicle systems 33, 36,
`
`41, and 42 that are affected depending on the identified exterior. (Ex. 1102, Fig. 1,
`
`5:31-6:8; Ex. 1103, pp. 12-14.)
`
`Lemelson renders obvious claims 10 and 23 of the ’000 patent. First, Lemelson
`
`teaches element a “transmitter means for transmitting . . . ”, element 10(a) (element
`
`23(a) is substantially the same). The Board construed this term to cover “infrared,
`
`radar, and pulsed GaAs laser systems” as well as “transmitters which emit visible light.”
`
`(IPR2013-00424 Institution Decision, p 19.) Lemelson teaches vehicle headlights
`
`which are within that construction because they “emit visible light.” (Ex. 1102, 3:29,
`
`5:57; Ex. 1103, pp. 9, 13.) Vehicle headlights also satisfy the “infrared” element of that
`
`construction because ordinary headlights emitted infrared waves when Lemelson was
`
`filed (and at the time the ’304 app. was filed). (Ex. 1109, ¶ 49.) Lemelson also
`
`discloses “infrared imaging,” which teaches receiving infrared waves, including those
`
`emitted by headlights. (Ex. 1102, 6:36-37; Ex. 1103, p. 14.) Lemelson also discloses
`
`“radar and/or laser range signals” transmitted by the vehicle which also satisfies the
`
`Board’s construction. (Ex. 1102, 6:2-3; Ex. 1103, p. 9.)
`
`
`
`10
`
`

`

`Lemelson teaches a “reception means . . .”, element 10(b) (elements 16(a) and
`
`23(b) are substantially the same). The Board construed this term to cover “a CCD
`
`array and a CCD transducer.” (IPR2013-00424 Institution Decision, p. 20.) Lemelson
`
`teaches that TV cameras are preferably CCD arrays that receive electromagnetic
`
`radiation from exterior objects, thus satisfying the Board’s construction. (Ex. 1102,
`
`5:31, 6:31-32; Ex. 1103, pp. 12-14.) The imaging method may include “infrared
`
`imaging.” (Ex. 1102, 6:36; Ex. 1103, p. 14; see also Ex. 1102, 4:13; Ex. 1103, p. 10.)
`
`Lemelson teaches a “processor means . . .”, element 10(c) (elements 16(b) and
`
`23(c) are substantially the same). In particular, Lemelson teaches that “[t]he analog
`
`signal output of camera 16 is digitized in an A/D convertor 18 and passed directly to
`
`or through a video preprocessor 51 to microprocessor 11, to an image field analyzing
`
`computer 19 which is provided, implemented and programmed using neural networks
`
`and artificial intelligence.” (Ex. 1102, 5:36-41, Figs. 1 and 2; Ex. 1103, p. 9, Figs. 1 and
`
`2.) This teaches that the reception means (a camera) is “coupled to” the processor
`
`means (Ex. 1109, ¶ 52) as well as “creating an electronic signal characteristic of said
`
`exterior object” because digitizing the analog signals received by the camera using an
`
`“A/D converter” requires creating a digital signal representative (“characteristic”) of
`
`the waves received. (Ex. 1109, ¶ 52.)
`
`Lemelson teaches a “categorization means . . .”, element 10(d) (elements 16(c)
`
`and 23(d) are substantially the same). (Ex. 1109, ¶¶ 53-56.) The Board construed this
`
`to mean “a neural computer, a microprocessor, and their equivalents.” (IPR2013-
`
`
`
`11
`
`

`

`00424 Institution Decision, p. 22.) Lemelson teaches that the camera signal is passed
`
`“to microprocessor 11, to an image field analyzing computer 19 which is provided,
`
`implemented and programmed using neural networks.” (Ex. 1102, 5:36-38; Ex. 1103,
`
`p. 9.)
`
`Lemelson’s categorization means also comprises “trained pattern recognition
`
`means . . . .” The Board construed this term to cover “a neural computer or
`
`microprocessor trained for pattern recognition, and equivalents thereof.” See Section
`
`III.C. Lemelson satisfies this limitation for the same reason as the “categorization
`
`means.” (Ex. 1109, ¶¶ 53-56.)
`
`Lemelson teaches that the trained pattern recognition means is “structured and
`
`arranged to apply a pattern recognition algorithm.” The Board construed “pattern
`
`recognition algorithm” as “an algorithm which processes a signal that is generated by
`
`an object, or is modified by interacting with an object, for determining to which one of
`
`a set of classes the object belongs.” The neural networks taught by Lemelson are
`
`within the Board’s construction because neural networks, by design, ascribe a label to
`
`input data and thus necessarily “determine to which one of a set of classes the object
`
`belongs.” (Ex. 1109, ¶¶ 45, 53-56.) The Board construed “identify” to mean “to
`
`determine that the object belongs to a particular set or class.” See Section III.C. In this
`
`regard, Lemelson teaches “identifying objects on the road ahead such as other vehicles,
`
`pedestrians,” (Ex. 1102, col. 5:41-42; Ex. 1103, p. 9), which means determining that the
`
`object belongs to a particular set or class such as vehicles, pedestrians, etc., (Ex. 1109,
`
`
`
`12
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`

`

`¶¶ 45, 56).
`
`Claims 10 also recites that the trained pattern recognition means is structured
`
`and arranged to apply a pattern recognition “algorithm generated from data of possible
`
`exterior objects . . .” Claim 23 includes a similar phrase. Even if this method step
`
`within a system claim (claim 10) constitutes a limitation (see MPEP § 2113; SmithKline
`
`Beecham Corp. v. Apotex Corp., 439 F.3d 1312, 1317 (Fed. Cir. 2006) (en banc); Ex Parte
`
`Klasing et al., App. No. 11/507,120, 2013 Pat. App. LEXIS 1619, at *8-10 (PTAB
`
`March 14, 2013)), and even if is limited to training with “real data,” it would have been
`
`obvious to one of ordinary skill in view of Lemelson.
`
`Lemelson already discloses that the neural network is trained with “known
`
`inputs.” (Ex. 1102 at 8:1-8; Ex. 1103 at pp. 16-17.) In the early-to-mid 1990s, one of
`
`ordinary skill in the art would have known that training with “real data” would have
`
`yielded the best results for this purpose of training the Lemelson system. (Ex. 1109 at
`
`¶ 57-66.) The Lemelson neural network was trained to identify “other vehicles,
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`pedestrians, barriers and dividers, turns in the road, signs and symbols.” (Ex. 1109 at ¶
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`64.) As of 1995, one of ordinary skill in the art would not have expected that a
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`simulated data set could be readily generated that could accurately represent all exterior
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`objects described by Lemelson as perceived by sensors on a vehicle. (Ex. 1109 at ¶ 64.)
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`One of ordinary skill in the art in 1995 would have known that the generation of
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`simulated data was not sophisticated enough to allow for training the type of neural
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`network described by Lemelson. (Ex. 1109 at ¶ 61.) Generation of simulated data
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`would have required a lot of computer power and special equipment, neither of which
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`were disclosed by Lemelson. (Ex. 1109 at ¶ 63.) Lemelson does not disclose any
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`computer hardware or methods for generating simulated data. (Id.)
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`Moreover, images directly obtained from exterior objects would have been by
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`far more representative of the types of complex 3-dimensional objects Lemelson’s
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`vehicle warning system would have been expected to encounter during road operation.
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`(Ex. 1109 at ¶ 65.) Such data would also have been far more plentiful, easier to obtain,
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`less costly and less time-consuming to produce than any synthetic data then available.
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`(Ex. 1109 at ¶ 65.) Additionally, one of ordinary skill would not have expected to
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`succeed in training a neural network to accurately recognize (as would be required of a
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`vehicle warning system) complex 3-dimensional objects like pedestrians, automobiles,
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`trucks, etc. without using sufficiently representative data, which could only have been
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`obtained from exterior objects directly imaged. (Ex. 1109 at ¶ 65.) Accordingly, the
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`“generated from” phrase would have been obvious to one of ordinary skill.
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`Lemelson discloses an “output means . . . ”, element 10(e) (element 23(e) is
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`substantially the same). The Board construed this as an “electronic circuit or circuits
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`capable of outputting a signal to another vehicle system.” Lemelson teaches this
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`through its disclosure of a processor (decision computer 23) that accepts codes from
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`the image analysis computer 19 and “integrates the inputs from the image analysis
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`computer 19” as well as from a “radar or lidar computer 14.” (Ex. 1102, 8:30-33, 6:1-8;
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`Ex. 1103, pp. 9, 13-14.) The decision computer 23 performs the function of “affecting
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`14
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`a system in the vehicle” by generating control signals to control a vehicle system such
`
`as the brakes or steering wheel. (Ex. 1102, 5:46-52; Ex. 1103, pp. 8-9.) Based on the
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`codes provided by the image-analyzing computer 19, the decision computer 23 can also
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`operate a heads-up display viewable by the driver or a warning light. (Ex. 1102, 5:45-
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`56; Ex. 1103, pp. 8-9.) A decision computer that generates control signals to vehicle
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`systems such as brakes, steering or a warning display would necessarily be an
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`“electronic circuit or circuits capable of outputting a signal to another vehicle system.”
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`(Ex. 1109, ¶ 67.) Thus, Lemelson renders claims 10 and 23 obvious because it teaches
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`every limitation of those claims.
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`Claim 11 depends directly from claim 10 and recites a “measurement means for
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`measuring the distance from the at least one exterior object to said vehicle, said
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`measurement means comprising radar.” Lemelson satisfies this because it discloses
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`that “[a]n auxiliary range detection means comprises a range computer 21 which
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`accepts digital code signals from a radar or lidar computer 14 which interprets radar
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`and/or laser range signals from respective reflected radiation receiving means on the
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`vehicle.” (Ex. 1102, 5:67-6:8; Ex. 1103, p. 9.) Lemelson also teaches “distance
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`measurements from radar/lidar systems” and thus renders claim 11 obvious. (Ex.
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`1102, 8:55-58; Ex. 1103, p. 14; Ex. 1109, ¶ 68.)
`
`Claim 19 depends from claim 10, and requires that the “reception means
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`comprise a CCD array.” As discussed above, Lemelson satisfies this limitation at least
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`through its disclosure that the “video camera 16 is preferably a CCD array.” (Ex.
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`
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`15
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`

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`1102, 6:31-32; Ex. 1103, p. 10; Ex. 1109, ¶ 70.)
`
`Claim 23 recites substantially the same limitations as claim 10 (as stated above)
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`except in method claim form. Claim 23 does not expressly include the “trained pattern
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`recognition” limitation recited in element 10(d). Claim 23 instead requires “processing
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`the electronic signal” by “generating a pattern recognition algorithm,” “storing the
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`algorithm within the pattern recognition system,” and “applying the pattern recognition
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`algorithm.” For the reasons discussed above, Lemelson satisfies these limitations. (Ex.
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`1109, ¶¶ 53-66.) As shown in the below claim charts, Lemelson teaches each and every
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`element of claims 10, 11, 19, and 23.
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`
`
`’000 Patent – Claim 10
`10. In a motor vehicle
`having an interior and an
`exterior, a monitoring
`system for monitoring at
`least one object exterior
`to said vehicle
`comprising:
`
`a) transmitter means for
`transmitting
`electromagnetic waves to
`illuminate the at least one
`exterior object;
`
`
`
`
`
`
`
`
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`Lemelson (Ex. 1102); ’304 Application (Ex. 1103)
`E.g., Ex. 1102, Fig. 1; see also Ex. 1103, Fig. 1.
`E.g., Ex. 1102, 2:14-20, “a video scanning system, such as
`a television camera and/or one or more laser scanners
`mounted on the vehicle scan the road in front of the
`vehicle and generate image information which is computer
`analyzed per se or in combination with a range sensing
`system to warn the driver of hazardous conditions during
`driving by operating a display.” See also Ex. 1103, p. 3.
`
`E.g., Ex. 1102, 4:8-15, “Another object is to provide a
`system and method employing a television scanning
`camera mounted on a vehicle for scanning the field ahead,
`such as the image of the road ahead of the vehicle and a
`computer for analyzing the image signals generated
`wherein automatic image intensifying, or infra-red
`scanning and detection means is utilized to permit
`scanning operations to be effected during driving at night
`and in low light, snowing or fog conditions.” See also Ex.
`1103, p. 6.
`E.g., Ex. 1102, 6:34-37, “The video camera 16 may also be
`implemented with other technologies including known
`16
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`

`b) reception means for
`receiving reflected
`electromagnetic
`illumination from the at
`least one exterior object;
`
`c) processor means
`coupled to said reception
`means for processing
`said received illumination
`and creating an electronic
`signal characteristic of
`said exterior object based
`thereon;
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`
`
`
`
`
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`
`
`
`
`
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`
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`image intensifying electron gun and infrared imaging
`methods.” See also Ex. 1103, p. 10.
`E.g., Ex. 1102, 5:56, “[A] head light controller 41.” See
`also Ex. 1103, p. 9.
`
`E.g., Ex. 1102, Figs. 1-2. See also Ex. 1103,
`Figs. 1-2.
`E.g., Ex. 1102, 5:31-39, “A television camera(s) 16 having a
`wide angle lens 16L is mounted at the front of the vehicle
`such as the front end of the roof, bumper or end of the
`hood to scan the road ahead of the vehicle . . . The analog
`signal output of camera 16 is digitized in an A/D
`convertor 18 and passed directly to or through a video
`preprocessor 51 to microprocessor 11, to an image field
`analyzing computer 19.” See also Ex. 1103, pp. 8-9.
`E.g., Ex. 1102, 6:37-38, “Multiple cameras may be used for
`front, side and rear viewing and for stereo imaging
`capabilities.” See also Ex. 1103, p. 10.
`
`E.g., Ex. 1102, Figs. 1-4. See also Ex. 1103,
`Figs. 1-4.
`E.g., Ex. 1102, 5:36-45, “The analog signal output of
`camera 16 is digitized in an A/D convertor 18 and passed
`directly to or through a video preprocessor 51 to
`microprocessor 11, to an image field analyzing computer
`19, which is provided, implemented and programmed
`using neural networks and artificial intelligence as well as
`fuzzy logic algorithms to (a) identify objects on the road
`ahead such as other vehicles, pedestrians, barriers and
`dividers, turns in the road, signs and symbols, etc., and
`generate identification codes, and (b) detect distances from
`such objects by their size (and shape).” See also Ex. 1103,
`pp. 8-9.
`E.g., Ex. 1102, 6:10-11, “The image analyzing computer 19
`with associated memory 20 may be implemented in several
`different ways.” See also Ex. 1103, p. 9.
`E.g., Ex. 1102, 7:47-48, “In another embodiment, the
`image analyzing computer 19 is implemented as a neural
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`d) categorization
`means coupled to said
`processor means for
`categorizing said
`electronic signal to
`identify said exterior
`object, said
`categorization means
`comprising trained
`pattern recognition
`means for processing
`said electronic signal
`based on said received
`illumination from said
`exterior object to
`provide an identification
`of said exterior object
`based thereon, said
`pattern recognition
`means being structured
`and arranged to apply a
`pattern recognition
`algorithm generated
`from data of possible
`exterior objects and
`patterns of received
`electromagnetic
`illumination from the
`possible exterior objects;
`and
`
`e) output means coupled
`to said categorization
`means for affecting
`another system in the
`
`
`
`
`
`
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`computing network. . . .” See also Ex. 1103, p. 12.
`See disclosure