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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 1 of 31
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 2 of 31
`
` IN THE UNITED STATES DISTRICT COURT
` WESTERN DISTRICT OF TEXAS
` WACO DIVISION
`
` GENTEX CORPORATION and )
` INDIGO TECHNOLOGIES, LLC, )
` )Case No.
` Plaintiffs, )6:21-cv-00755-ADA
` )
` THALES VISIONIX, INC., )
` )
` Involuntary )
` Plaintiff, )
` )
` v. )
` )
` FACEBOOK, INC. and FACEBOOK )
` TECHNOLOGIES, LLC, )
` )
` Defendants. )
` ______________________________)
`
` REMOTE PROCEEDINGS OF THE
` VIDEOTAPED DEPOSITION OF JOSEPH LAVIOLA, PH.D.,
` WEDNESDAY, MARCH 30, 2022
`
` REPORTED BY NANCY J. MARTIN
` CSR. NO. 9504, RMR, RPR
`
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 3 of 31
`
` IN THE UNITED STATES DISTRICT COURT
` WESTERN DISTRICT OF TEXAS
` WACO DIVISION
`
` GENTEX CORPORATION and )
` INDIGO TECHNOLOGIES, LLC, )
` )Case No.
` Plaintiffs, )6:21-cv-00755-ADA
` )
` THALES VISIONIX, INC., )
` )
` Involuntary )
` Plaintiff, )
` )
` v. )
` )
` FACEBOOK, INC. and FACEBOOK )
` TECHNOLOGIES, LLC, )
` )
` Defendants. )
` ______________________________)
`
` - - -
` WEDNESDAY, APRIL 30, 2022
` - - -
`
` Videotaped Deposition of JOSEPH LAVIOLA, PH.D.,
` beginning at 9:00 a.m., before Nancy J. Martin, a
` Registered Merit Reporter, Certified Shorthand
` Reporter. All parties appeared remotely.
`
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 4 of 31
`
` A P P E A R A N C E S :
`
` J O S H U A G L U C O F T , E S Q .
` B A I L E Y W A T K I N S , A T T O R N E Y A T L A W
` K I R K L A N D & E L L I S L L P
` 5 5 5 C a l i f o r n i a S t r e e t
` S u i t e 2 7 0 0
` S a n F r a n c i s c o , C a l i f o r n i a 9 4 1 0 4 - 1 5 0 3
` ( 3 1 0 ) 5 5 2 - 4 2 8 4
` j o s h . g l u c o f t @ k i r k l a n d . c o m
` C o u n s e l f o r D e f e n d a n t s
`
` A D A M H A R B E R , E S Q .
` S H A Y O N G H O S H , E S Q .
` W I L L I A M S & C O N N O L L Y L L P
` 7 2 5 1 2 t h S t r e e t N W
` W a s h i n g t o n , D . C . 2 0 0 0 5
` a h a r b e r @ w c . c o m
` ( 2 0 2 ) 4 3 4 - 5 8 2 0
` C o u n s e l f o r P l a i n t i f f s
`
` A L S O P R E S E N T :
` O R S O N B R A I T H W A I T E , L E G A L V I D E O G R A P H E R
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 5 of 31
`
` I N D E X
`
` TESTIMONY OF JOSEPH LAVIOLA PAGE
`
` BY MR. GLUCOFT 6
`
` E X H I B I T S
` NUMBER DESCRIPTION MARKED
` Exhibit 1 DECLARATION OF JOSEPH J. 11
` LAVIOLA JR./REGARDING
` CLAIM CONSTRUCTION, 110
` pages
`
` Exhibit 2 US 6,922,632 B2, 40 pages 23
`
` Exhibit 3 US 6,757,068 B2, 16 pages 23
`
` Exhibit 4 AgileSLAM: A Localization 42
` Approach for Agile Head
` Movements in/Augmented
` Reality, 6 pages
` Exhibit 5 A Comparison of Unscented 117
` and Extended
` Kalman/Filtering for
` Estimating Quaternion
` Motion, 6 pages
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 6 of 31
`
` technologies that require a -- something that -- that
`
` we often call an "emitter."
`
` The emitter sends out signals. So it could
`
` send out an electromagnetic field, for example. It
`
` could send out a set of, you know, acoustic signals.
`
` And typically, with these types of tracking systems
`
` there's something known as a receiver and that's the
`
` thing that you usually would put on your head or you
`
` put on your hand to track. But there would always be
`
` this emitter that sort of is put in the room that
`
` sends out the signals. So that's like where the point
`
` of reference is.
`
` Certain tracking technologies don't require
`
` an emitter. The sensors themselves are able to
`
` generate information, data, about the -- often it
`
` gives you things like motion, motion information,
`
` things like acceleration and velocity, magnet --
`
` magnetic information from, you know, magnetic field in
`
` the north, and it doesn't require any external emitter
`
` to provide that information.
`
` So those types of tracking systems can be put
`
` on the body, for example, on the head or held in your
`
` hand, what have you, and there's no restriction on
`
` where you can go with it because it is computing or
`
` sensing its velocity or acceleration of the actual
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 7 of 31
`
` could say that there could be any point on the game
`
` controller that could be considered a localized
`
` feature.
`
` Q. What's the difference between a feature and a
`
` localized feature?
`
` A. A feature is a -- so when we talk about the
`
` word "feature" in this context, we're talking about
`
` something, an entity, piece of something that can be
`
` used to discriminate itself from other things. Okay?
`
` A localized feature, in the context of this
`
` patent, is one that has to do with the hand or
`
` something being held on the hand or something being
`
` held or something being placed on the hand. The held
`
` put on the hand or the hand itself, or any other limb
`
` for that matter. It could be a foot. As it turns --
`
` as opposed to, you know, an overall feature, you know,
`
` something that describes everything.
`
` This is just describing a small piece of the
`
` object that's being tracked. That's why it's
`
` localized.
`
` Q. So in the context of these patents, can you
`
` be a localized feature if you're not associated with a
`
` limb?
`
` A. Can you be a localized feature and not
`
` associated with a limb. I believe in the context of
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 8 of 31
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` these patents and the particular claim term, if it's
`
` not associated with a limb, meaning that it's not
`
` something on the hand, held in the hand, or attached
`
` to the hand or other limb, then it would not be a
`
` localized feature.
`
` Q. So in this patent, all localized features are
`
` associated with a limb?
`
` MR. HARBER: Objection. Vague.
`
` THE WITNESS: They're -- I believe in the
`
` context of these patents that a localized feature is
`
` associated with the limb -- a limb of the user.
`
` BY MR. GLUCOFT:
`
` Q. So a feature -- a localized feature is
`
` necessarily associated with a limb in these patents?
`
` MR. HARBER: Objection. Vague.
`
` THE WITNESS: I mean I believe that to be
`
` true.
`
` BY MR. GLUCOFT:
`
` Q. So when the claim -- excuse me. Strike that.
`
` When the claims recite a localized feature,
`
` those localized features are inherently associated
`
` with a limb?
`
` MR. HARBER: Objection. Misstates the
`
` testimony.
`
` THE WITNESS: I mean the term says, you know,
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 9 of 31
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` what it is. A localized feature is associated with a
`
` limb of the user. That's what it says. I mean I
`
` don't -- you know...
`
` BY MR. GLUCOFT:
`
` Q. Right. I'm just asking about a localized
`
` feature. Is there a thing known as a localized
`
` feature that is not associated with a limb in the
`
` context of these patents?
`
` A. I don't believe so.
`
` Q. What criteria do you use to evaluate whether
`
` a feature is associated with a limb of the user?
`
` A. I mean I -- I look at it more in the context
`
` of the hand than the foot or knee or whatever. So in
`
` that respect, you know, a localized feature is --
`
` that's associated with the limb of a user is going to
`
` be one that is mounted on the hand. It's going to be
`
` either mounted on the hand, either going to be held on
`
` the hand -- in the hand, or it's going to be the hand
`
` itself.
`
` Q. Okay. So to be associated with a limb, it
`
` needs to either be mounted on the limb, held by the
`
` limb, or part of a limb itself?
`
` A. Yes.
`
` Q. Can the localized feature be something that
`
` extends out from the limb?
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 10 of 31
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` A. Could you provide an example?
`
` Q. Sure. So let's say a piece of rope. Is that
`
` associated with a limb when it's held in someone's
`
` hand?
`
` A. I mean the -- you could say that a piece of
`
` rope is -- that is held in the hand would be
`
` associated with a limb. You could say that.
`
` Q. Would the portions of the rope that are not
`
` in physical contact with the hand also be associated
`
` with the limb?
`
` A. In the context of these patents, when the
`
` point is that you want to track something, the object
`
` that you're holding in your hand would have to be one
`
` that -- that could be tracked. Okay? And if it's not
`
` a rigid object, then you wouldn't be able to
`
` reasonably track that object.
`
` So even though you're holding a piece of the
`
` rope in your hand -- right? -- and you could get, you
`
` know, a localized feature of the rope being held in
`
` the hand, you wouldn't be able to necessarily track
`
` that feature because it's a non-rigid object.
`
` Q. Okay. So when a user of the system is
`
` holding a piece of rope, only the portion of the rope
`
` that's actually in the end user's hand is associated
`
` with a limb and the rest is not?
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 11 of 31
`
` A. I mean if...
`
` (The witness reviewed the document.)
`
` THE WITNESS: So you would ideally be able to
`
` track a rigid object, like a tennis racket, for
`
` example, and because of its rigidity, you would be
`
` able to find features, localized features that you
`
` could use for tracking purposes.
`
` But with a rope, for example, anything that
`
` does not have that rigid characteristic, you know,
`
` that rigid structure, then it -- I don't believe in
`
` the scope of these patents it would be considered a
`
` localized feature that would be -- that you would
`
` track.
`
` BY MR. GLUCOFT:
`
` Q. All right. So do you agree that the portion
`
` of the rope in the user's hand is associated with the
`
` limb?
`
` A. I mean one could say that that piece --
`
` right? -- is -- would be associated with the hand.
`
` You're holding it. So it's associated with the hand.
`
` Q. Any portion of the rope that's not in the
`
` hand is not associated with the limb?
`
` A. For this particular example, this particular
`
` object or any object that's non-rigid, then I would
`
` say that it's not associated with the hand.
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 12 of 31
`
` Q. How many different second positions can there
`
` be?
`
` MR. HARBER: Objection. Vague.
`
` THE WITNESS: I mean infinite.
`
` BY MR. GLUCOFT:
`
` Q. Can you please look at Claim 56 of the '068
`
` patent. You didn't render any opinions on
`
` infringement in this case; correct?
`
` A. I didn't render any opinions of infringement
`
` on this case? No.
`
` Q. So you don't have any opinion as to whether
`
` Meta's Oculus products are within the scope of
`
` Claim 56; correct?
`
` A. That's correct.
`
` Q. Could an Oculus system be within the scope of
`
` Claim 56?
`
` MR. HARBER: Objection. The witness just
`
` said he didn't have opinions on this.
`
` THE WITNESS: I would have to study it.
`
` BY MR. GLUCOFT:
`
` Q. Could any system be within the scope of
`
` Claim 56?
`
` MR. HARBER: Same objection.
`
` THE WITNESS: I mean, once again, I would
`
` have to study the particulars to form an opinion on
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 13 of 31
`
` utility.
`
` Q. What about in those other approaches you were
`
` talking about, like SLAM and --
`
` A. SLAM has elements of -- like I said elements
`
` of Kalman filtering in it. So it probably would
`
` require -- there's probably -- I don't know off the
`
` top of my head, a measure in the SLAM algorithm that
`
` you could use to determine what the expected or
`
` highest expected utility is.
`
` As far as some of the other things, you know,
`
` like I said, the programmer is going to bring to
`
` bear -- a person of ordinary skill in the art is going
`
` to bring to bear a set of knowledge about tracking
`
` systems, prediction and estimation and would come
`
` to -- you know, utilizing that knowledge would --
`
` could develop algorithms that would, you know, provide
`
` you what could be considered the highest expected
`
` utility.
`
` Q. Why do you say, it "could be considered"? Is
`
` there no objective highest expected utility?
`
` A. I mean it's in the -- in this case, it's in
`
` the eyes of the programmer; right? So if the
`
` programmer is using something that is going to compute
`
` an optimal instructed utility, then that would be the
`
` highest expected utility.
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 14 of 31
`
` term that you were referring to.
`
` Q. So providing any information at all would
`
` characterize the state estimate?
`
` A. I mean if you provide some information, it's
`
` going to give you some understanding of the state
`
` estimate. You could provide different types of
`
` information, and you might do well to be better
`
` categorization -- you know, characterizing or not so
`
` good at characterizing, but you're still attempting to
`
` characterize the state estimate.
`
` Q. Can you characterize an input device?
`
` A. I believe that -- that you can characterize
`
` an input device.
`
` Q. Is one way to characterize an input device by
`
` the input type and frequency of the data they
`
` generate?
`
` A. Yes.
`
` Q. What information is required to characterize
`
` an estimate of a location?
`
` A. This is an example of a place where a
`
` characterizes can also be thought of as using the --
`
` the term "is." So an estimate is an estimate of a
`
` location of the object.
`
` Q. Okay. Are you saying that in some instances
`
` to characterize information such as the estimate of a
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`Case 6:21-cv-00755-ADA Document 48-2 Filed 04/01/22 Page 15 of 31
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` location, that means actually provide that
`
` information, but in other instances characterizes
`
` means to describe the information?
`
` MR. HARBER: Objection. Misstates the
`
` testimony.
`
` THE WITNESS: The way I see it is that the
`
` word, you know, "characterizes" can mean different
`
` things depending on context. So in some cases it
`
` means it's to describe. Sometimes it means, you know,
`
` that it represents using the word "is," and one of the
`
` things that -- that the test, at least that I use, is
`
` I replace the word "characterize" with those words,
`
` "described" or "is," and then determine which one is
`
` more appropriate.
`
` BY MR. GLUCOFT:
`
` Q. Okay. So in the '632 patent, in which claims
`
` does characterize mean describe and in which claims
`
` does characterize mean is?
`
` A. Okay. Well, in Claim 5 we have "the state
`
` estimate characterizes an estimate of" the "location
`
` of the object." So we say that the state estimate is
`
` an estimate of the location of an object. Okay?
`
` In Claim 6, "the state estimate characterizes
`
` configuration informing for one or more sensing
`
` elements fixed to the object."
`
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` characterizes in Claims 5 and 60 means is, but in
`
` Claims 6, 13, 17, 18, 19, 59 and 61 it means
`
` describes; is that correct?
`
` A. That's how I interpret it.
`
` Q. And there is a difference between when
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` characterized means is versus when characterized means
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` describes; right?
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` MR. HARBER: Objection. Misstates the
`
` testimony.
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` THE WITNESS: I think if you were to look up
`
` the definition of the word "characterizing," I would
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` assume that you would find a number of different
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` definitions for it. I think, you know, is and then
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` characterizing is -- or describing is -- they're
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` similar, but, you know, they do provide some level of
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` distinctness with the term.
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` BY MR. GLUCOFT:
`
` Q. And the distinctness is that the description
`
` of the data is not the data itself; right?
`
` A. Uh-huh. Yes. Sorry.
`
` Q. Could you please turn to Paragraph 64 of your
`
` declaration. You say here, "Dr. Bobick contends that
`
` the words 'characterizes' and 'characterizing' have a
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` 'commonly understood meaning in the field of computer
`
` vision and tracking in situations where it is clear
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` that they are referring specifically to describe
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` uncertainty or noise characteristics in measurement.'
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` I disagree. From the context of the claims, and even
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` more so from the disclosures in the specifications
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` cited above, a POSITA would have recognized that the
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` claims use the words in their common English sense."
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` So when you say you disagree, are you
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` disagreeing about what the commonly understood meaning
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` is in the field of computer vision and tracking, or
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` are you saying that you disagree as to whether that
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` definition or the common English sense definition
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` should apply?
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` A. I disagree in -- in terms of the use of the
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` common sense -- common English sense.
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` So in computer vision and other fields, we
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` can talk about noise characteristics. Okay. Noise
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` characteristics means could be the noise could be
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` white. It could be colored. It's a variety of
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` different things. People talk about that as -- you
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` know, in the field.
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` But in all the terms in these claims, they're
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` all using the term in its common English sense.
`
` Q. So as far as the technical definition in the
`
` field that Dr. Bobick provided, you're not disagreeing
`
` with his definition of characterizes. You're just
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` saying that the technical definition doesn't apply.
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` It's the common, look it up in a regular dictionary
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` sense?
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` A. Yes.
`
` Q. And so how would a person of ordinary skill
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` know that the non-technical definition applies as
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` opposed to the definition from the field?
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` MR. HARBER: I just think you're misstating
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` the testimony and what his declaration says, but...
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` THE WITNESS: Anyone of ordinary skill in the
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` art could tell where that word "characterize" is being
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` used; right? Also notice, you know, the -- the word
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` "characterize" is used after the -- the noun. So
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` noise characteristic; right? And in all of the claims
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` it's being used as sort of like a verb, if you will,
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` between two noun phrases saying one thing describes
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` another thing, or one thing is described by another
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` thing.
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` So I think it's pretty straightforward that a
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` person of ordinary skill in the art would be able to
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` tell the difference between the two.
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` MR. GLUCOFT: Okay. Why don't we take a
`
` 20-minute lunch break. Does that work?
`
` THE WITNESS: Sure.
`
` THE VIDEOGRAPHER: The time is 12:39 p.m.
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` This ends Unit 3. We're off the record.
`
` (A recess was taken from 12:39 p.m.
`
` to 1:09 p.m.)
`
` THE VIDEOGRAPHER: The time is 1:09 p.m.
`
` This begins Unit No. 4. We're on the record.
`
` BY MR. GLUCOFT:
`
` Q. Dr. LaViola, what is an estimation module?
`
` (The witness reviewed the document.)
`
` THE WITNESS: An estimation module, in terms
`
` of the claims in this patent, they refer to a
`
` component, a software component that accepts sensor
`
` and configuration and measurement information and
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` updates a state estimate using all or some of that
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` information.
`
` BY MR. GLUCOFT:
`
` Q. Did estimation module have a well understood
`
` meaning in the art at the time of the Family 2
`
` patents?
`
` A. I wouldn't say it had an accepted meaning in
`
` the art, but when you talk about the term "estimation
`
` module" in the art, you pretty much know that it's
`
` going to be doing something having to do with
`
` estimating a pose.
`
` Q. So then is it your opinion that the Family 2
`
` patents define what an estimation module is?
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` has a common definition; right? But everybody who
`
` would hear that term would know that you were talking
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` about doing a pose estimate in a tracking system, in
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` that context, in the context of VR motion tracking
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` systems.
`
` Q. Would they all know how an estimation module
`
` does that pose estimate?
`
` A. Those people in the art who had previously
`
` built tracking systems probably would, you know, know
`
` how to -- to do that. Other people who hadn't would
`
` need to read the patent and the specification to get a
`
` good understanding of -- of how to do it.
`
` Q. So was an estimation module a conventional
`
` structure known in the prior art at the time of the
`
` Family 2 patents?
`
` MR. HARBER: Objection. Vague.
`
` THE WITNESS: I mean it's not like I could
`
` go, you know, to the local store and pick up an
`
` estimation module or anything like that, you know, but
`
` it's a term that implies that -- it implies there's a
`
` software component, and it implies that component is
`
` going to have in it a necessary infrastructure to
`
` support estimating a pose.
`
` BY MR. GLUCOFT:
`
` Q. So an estimation module wasn't an
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` So I'm just trying to make sure that I'm
`
` correct in thinking it's the same sensor fusion core
`
` that you are linking to both the estimation subsystem
`
` and the estimation module?
`
` A. It is.
`
` Q. Okay. Take a look at Claim 47, please.
`
` A. Claim 47.
`
` Q. So you see it at the end it says,
`
` "maintaining estimates of tracking parameters in the
`
` estimation module, including repeatedly," and then it
`
` lists some steps?
`
` A. Yes.
`
` Q. Where in the specification would you find an
`
` algorithm for performing those maintaining steps?
`
` (The witness reviewed the document.)
`
` THE WITNESS: So going to Claim 47, as you
`
` stated, so it talks about "repeatedly passing data
`
` based on the estimates of the tracking parameters from
`
` the estimation module to one or more of the sensor
`
` modules."
`
` So if you look at Figure 2, you'll see that
`
` in the sensor fusion core, which is also considered to
`
` be the estimation module, there are bidirectional
`
` links to the meta drivers, and ultimately, to the
`
` PSEs, which represent the sensors.
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` BY MR. GLUCOFT:
`
` Q. Yes.
`
` A. I don't think -- that is a necessary but not
`
` sufficient condition.
`
` MR. GLUCOFT: Okay. I think we can take a
`
` break for five minutes.
`
` THE VIDEOGRAPHER: The time is 2:15 p.m.
`
` This concludes Unit 4.
`
` (A recess was taken from 2:15 p.m.
`
` to 2:24 p.m.)
`
` THE VIDEOGRAPHER: The time is 2:24. We're
`
` back on the record.
`
` BY MR. GLUCOFT:
`
` Q. What's an estimation subsystem?
`
` (The witness reviewed the document.)
`
` THE WITNESS: So an estimation subsystem
`
` would essentially mean a subsystem component of some
`
` kind that accepts sensor configuration and measurement
`
` information and updates a state estimate using some or
`
` all of that information.
`
` BY MR. GLUCOFT:
`
` Q. Did estimation subsystem have an understood
`
` meaning in the art at the time of the Family 2
`
` patents?
`
` A. There wasn't -- I mean it's not a term that
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` is used -- or was used frequently in the art.
`
` However, the -- anyone of ordinary skill in the art
`
` would look at the term "estimation subsystem," and it
`
` would provide some information as to what the meaning
`
` of it is in terms of it being a -- you know, a
`
` subcomponent of a larger system that's job is to do
`
` estimation, or in this case, pose estimation.
`
` Q. So there wasn't a conventional structure
`
` known in the art associated with an estimated
`
` subsystem? Excuse me.
`
` There wasn't a conventional structure known
`
` in the art associated with an estimation subsystem; is
`
` that right?
`
` A. Yes, there was no, you know, estimation
`
` subsystem that was out there that you could -- you
`
` know, that everybody used.
`
` Q. So there wasn't any off-the-shelf component
`
` known as an estimation subsystem?
`
` A. No.
`
` Q. What is the structure of an estimation
`
` subsystem in the context of the Family 2 patents?
`
` (The witness reviewed the document.)
`
` THE WITNESS: So an estimation subsystem has
`
` a structure based on the claims and the specification.
`
` So it sort of repeatedly updates the state estimate,
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` them, and so on. So it could go all the way from just
`
` being a piece of hardware that you have to connect
`
` yourself all the way to hardware associated with a
`
` library that would allow for this communication.
`
` In the context of this patent, we're talking
`
` about a sensor module that has both the hardware and
`
` the appropriate software to communicate with the
`
` hardware.
`
` Q. So in the context of this patent, we're
`
` talking about a specific kind of sensor module that
`
` someone would have known in the art?
`
` A. I don't really consider it a specific kind of
`
` sensor module. It's just -- it's a sensor module
`
` that -- you know, that gives you the ability to --
`
` makes it easier for you to access the hardware than
`
` others. Some people want to be able to just have the
`
` individual, you know, sensors themselves so that they
`
` can stick them on an Arduino board or whatever.
`
` Some people want to go beyond that and have
`
` them and put them into a system and then, you know,
`
` have the code already there for it to communicate so
`
` that they can create their own driver that makes it
`
` easy to do the communication in. It depends on what
`
` you want.
`
` Q. Okay. So when -- I guess in the art at the
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`
` time of the Family 2 patents, the person of ordinary
`
` skill wants to go and pick up a sensor module. What's
`
` included in that sensor module then?
`
` A. As I said, it depends on the type of sensor
`
` module that you're buying.
`
` Q. Okay. And is the sensor module claimed in
`
` the Family 2 patents one of those types of sensor
`
` modules that we were just talking about?
`
` A. Yeah.
`
` Q. Okay. And which type is it?
`
` A. It would be the type that includes the
`
` appropriate software to allow the communication
`
` between the actual sensor hardware and any of the
`
` other subsystems in the tracking system.
`
` Q. And that type of sensor module was available
`
` off the shelf at the time?
`
` A. Yes.
`
` Q. And where would one go to get that kind of
`
` sensor module?
`
` A. I can't really recall specific places. I
`
` mean I know you couldn't go get it at Best Buy.
`
` Typically, they were offered online. Various
`
` companies sold them. I don't have any specific names.
`
` Q. Is "module" synonymous with "interface"?
`
` A. I wouldn't say it's synonymous with
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`
` refers to determining its position.
`
` BY MR. GLUCOFT:
`
` Q. So how do you localize an object?
`
` A. The same way you would track any other
`
` object. You would utilize the combination of the
`
` sensors and sensor subsystems, along with the
`
` estimation subsystem, to compute -- to update a s
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