Samsung Electronics Co., Ltd. et al., Petitioner
`
`(cid:89)(cid:17)
`
`Image Processing Technologies, LLC, Patent Owner
`
`(cid:44)(cid:51)(cid:53)(cid:21)(cid:19)(cid:20)(cid:26)(cid:16)(cid:19)(cid:20)(cid:21)(cid:20)(cid:27)
`(cid:51)(cid:68)(cid:87)(cid:72)(cid:81)(cid:87)(cid:3)(cid:49)(cid:82)(cid:17)(cid:3)(cid:27)(cid:15)(cid:28)(cid:27)(cid:22)(cid:15)(cid:20)(cid:22)(cid:23)
`
`(cid:51)(cid:68)(cid:87)(cid:72)(cid:81)(cid:87)(cid:3)(cid:50)(cid:90)(cid:81)(cid:72)(cid:85)(cid:182)(cid:86)(cid:3)(cid:39)(cid:72)(cid:80)(cid:82)(cid:81)(cid:86)(cid:87)(cid:85)(cid:68)(cid:87)(cid:76)(cid:89)(cid:72)(cid:86)
`(cid:45)(cid:88)(cid:81)(cid:72)(cid:3)(cid:21)(cid:28)(cid:15)(cid:3)(cid:21)(cid:19)(cid:20)(cid:27)(cid:3)(cid:50)(cid:85)(cid:68)(cid:79)(cid:3)(cid:36)(cid:85)(cid:74)(cid:88)(cid:80)(cid:72)(cid:81)(cid:87)
`
`Exhibit 2017
`IPR2017-01218
`Petitioner - Samsung Electronics Co., Ltd., et al.
`Patent Owner - Image Processing Technologies LLC
`1
`
`
`
`(cid:89)(cid:17)
`
`Image Processing Technologies, LLC, Patent Owner
`
`(cid:44)(cid:51)(cid:53)(cid:21)(cid:19)(cid:20)(cid:26)(cid:16)(cid:19)(cid:20)(cid:21)(cid:20)(cid:27)
`(cid:51)(cid:68)(cid:87)(cid:72)(cid:81)(cid:87)(cid:3)(cid:49)(cid:82)(cid:17)(cid:3)(cid:27)(cid:15)(cid:28)(cid:27)(cid:22)(cid:15)(cid:20)(cid:22)(cid:23)
`
`(cid:51)(cid:68)(cid:87)(cid:72)(cid:81)(cid:87)(cid:3)(cid:50)(cid:90)(cid:81)(cid:72)(cid:85)(cid:182)(cid:86)(cid:3)(cid:39)(cid:72)(cid:80)(cid:82)(cid:81)(cid:86)(cid:87)(cid:85)(cid:68)(cid:87)(cid:76)(cid:89)(cid:72)(cid:86)
`(cid:45)(cid:88)(cid:81)(cid:72)(cid:3)(cid:21)(cid:28)(cid:15)(cid:3)(cid:21)(cid:19)(cid:20)(cid:27)(cid:3)(cid:50)(cid:85)(cid:68)(cid:79)(cid:3)(cid:36)(cid:85)(cid:74)(cid:88)(cid:80)(cid:72)(cid:81)(cid:87)
`
`Exhibit 2017
`IPR2017-01218
`Petitioner - Samsung Electronics Co., Ltd., et al.
`Patent Owner - Image Processing Technologies LLC
`1
`
`
`
`Grounds Asserted in Petition
`
`Paper 2 (Petition) at 3.
`
`2
`
`
`
`’134 Patent, Claims 3–6 Depend from Claim 1
`
`[1pre] A process of tracking a target in an input signal
`implemented using a system comprising an image processing
`system, the input signal comprising a succession of frames,
`each frame comprising a succession of pixels, the target
`comprising pixels in one or more of a plurality of classes in one
`or more of a plurality of domains, the process performed by
`said system comprising, on a frame‐by‐frame basis:
`[1a] forming at least one histogram of the pixels in the one or
`more of a plurality of classes in the one or more of a plurality of
`domains, said at least one histogram referring to classes
`defining said target; and
`[1b] identifying the target in said at least one histogram itself,
`[1c] wherein forming the at least one histogram further
`comprises determining X minima and maxima and Y minima
`and maxima of boundaries of the target.
`
`Ex. 1001 (’134 Patent) at 28–29.
`
`3
`
`
`
`Claim Element [1c] is Dispositive of This IPR
`Under the Correct Phillips Construction
`
`[1a] “forming at least one histogram of
`the pixels in the one or more of a
`plurality of classes . . . said at least one
`histogram referring to classes defining
`said target”
`
`[1a] “forming at least one histogram of
`the pixels in the one or more of a
`plurality of classes in the one or more
`of a plurality of domains”
`[1c] “wherein forming the at least one
`histogram further comprises
`determining X minima and maxima
`and Y minima and maxima of
`boundaries of the target”
`
`“forming at least one histogram . . . at least one
`histogram being formed of pixels in the one or
`more classes that define said target.”
`
`“forming at least one histogram of the pixels in
`two or more classes that are in two or more
`domains.”
`
`This limitation requires that the formation of the
`histogram includes determining the X and Y
`boundaries of the target.
`
`Paper 15 (PO Resp.) at 19–39; Paper 34 (Supp. PO Resp.) at 1.
`
`4
`
`
`
`The Board is Not Bound by the IPR2017-00353
`Panel Result
`
`The IPR2017‐00353 Panel did not have the benefit of a
`complete record including:
`• The December 22, 2017 deposition of Samsung’s
`declarant, Dr. Hart
`• Patent Owner’s January 8, 2018 Response
`• Patent Owner’s May 31, 2018 Supplemental Reply
`
`Paper 34 (Supp. PO Resp.) at 1; Ex. 2011 (Hart Depo. Tr.) at 2; Exs. 2011–2016; Papers 15, 33.
`
`5
`
`
`
`’134 Patent, Dependent Claim 3
`
`Claim 3 depends from claim 1
`3. The process according to claim 1, wherein said image
`processing system comprises at least one component selected
`from a memory, a temporal processing unit, and a spatial
`processing unit.
`
`6
`
`
`
`’134 Patent, Dependent Claims 4–6
`
`Claim 4 depends from claim 1. Claims 5, 6 depend from claim 4:
`
`4. The process according to claim 1, wherein forming the at
`least one histogram further comprises successively increasing
`the size of a selected area until the boundary of the target is
`found.
`5. The process according to claim 4, wherein forming the at
`least one histogram further comprises adjusting a center of the
`selected area based upon a shape of the target until
`substantially the entire target is within the selected area.
`6. The process according to claim 5, wherein forming the at
`least one histogram further comprises setting the X minima and
`maxima and Y minima and maxima as boundaries in X and Y
`histogram formation units such that only pixels within the
`selected area will be processed by the image processing system.
`
`7
`
`
`
`Phillips Interpretation of Claim Element [1c]
`
`• Claim language
`
`• Specification
`
`• Prosecution History
`
`Paper 15 (PO Resp.) at 19; Paper 34 (Supp. PO Resp.) at 2.
`
`8
`
`
`
`Phillips Interpretation of Claim Element [1c]
`
`• Claim language
`
`• Specification
`
`• Prosecution History
`
`Paper 15 (PO Resp.) at 19; Paper 34 (Supp. PO Resp.) at 2.
`
`9
`
`
`
`Claim Element [1c]: Claim Language
`
`The plain language of the claim requires
`that “forming the at least one histogram . . .
`comprises determining . . . boundaries of
`the target”.
`
`Therefore, the claim requires locating
`boundaries of the target as part of forming
`the histogram.
`
`Paper 15 (PO Resp.) at 20, 23–25; Paper 34 (Supp. PO Resp.) at 1–2.
`
`10
`
`
`
`Element [1c]: Samsung’s Construction Allows
`Unlimited Post Histogram Computation
`
`Q. Is there any limitation on how much additional
`processing can be done after the histogram is
`formed in order to find boundaries?
`A. I don't see any limitation on the amount of
`computation or analysis. I think ’134, Claim 1 and
`specifically Element 1C says that you form a
`histogram and determine the X and Y minima and
`maxima as boundaries of the target.
`And I think that [if] determination is based on the
`formation of that histogram . . . then you satisfied the
`restrictions of Element 1C.
`
`Paper 34 (Supp. PO Resp.) at 1–2; Ex. 2011 (Hart Depo. Tr.), 115:11–23 (emphasis added).
`
`11
`
`
`
`Element [1c]: Samsung’s Construction Reads Out
`“Comprising” Claim Language
`
`Samsung’s interpretation reads out the “comprising”
`language, and would merely require a “forming” step
`and a “determining” step with no relationship
`between the steps. Essentially, Samsung reads the
`claim as:
`[1b] identifying the target in said at least one
`histogram itself, and
`[1c] wherein forming the at least one
`histogram further comprises determining X
`minima and maxima and Y minima and
`maxima of boundaries of the target.
`
`Paper 15 (PO. Resp.) at 23‐25; Paper 34 (Supp. PO Resp.) at 2.
`
`12
`
`
`
`Phillips Interpretation of Claim Element [1c]
`
`• Claim language
`
`
`
`• Specification
`
`• Prosecution History
`
`Paper 15 (PO Resp.) at 19; Paper 34 (Supp. PO Resp.) at 2.
`
`13
`
`
`
`’134 Patent Specification
`
`Separate embodiments:
`
`• Video conference embodiment
`– Figure 17 describes forming a histogram and then
`analyzing the histogram peaks
`
`• Lock-on tracking embodiment
`– Figures 20–23 describe an iterative process of
`finding boundaries during histogram formation for
`a single frame
`
`Paper 15 (PO Resp.) at 8–13, 26, 35, 37; Paper 34 (Supp. PO Resp.) at 4–5.
`
`14
`
`
`
`Video Conference Embodiment
`
`For the video
`conference
`embodiment,
`Figure 17
`describes
`forming
`histograms in
`order to find the
`face (V) center
`“at regular
`intervals”.
`
`Ex. 1001 at 13
`
`Ex. 1001 at 12
`
`Paper 15 (PO Resp.) at 26, 35; Paper 34 (Supp. PO Resp.) at 4; Ex. 1001 (’134 Patent), 23:23–24.
`
`15
`
`
`
`Video Conference Embodiment
`
`The video
`conference
`embodiment is
`like claim 59
`that was
`proposed and
`rejected during
`prosecution of
`the ’001 patent
`(parent to the
`’134 patent).
`
`Paper 34 (Supp. PO Resp.) at 4; Ex. 1022 (’001 patent prosecution) at 119.
`
`16
`
`
`
`Lock-on Tracking Embodiment
`
`The lock‐on tracking
`embodiment tracks a
`selected simulated
`object in an image.
`
`For example, the
`user selects object
`218 with the
`computer mouse.
`
`Ex. 1001 at 13
`
`Ex. 1001 at 15
`
`Paper 15 (PO Resp.) at 8–9; Paper 34 (Supp. PO Resp.) at 3–4.
`
`17
`
`
`
`Lock-on Tracking Embodiment
`
`The lock‐on tracking embodiment is an iterative
`process of finding boundaries during histogram
`formation
`
`Paper 15 (PO Resp.) at 10–11; Paper 34 (Supp. PO Resp.) at 2–4.
`
`18
`
`
`
`Lock-on Tracking Embodiment:
`Iterative Process of Forming a Histogram
`Q. …Exhibit 2014 is a portion of a frame of pixels….Does that
`make sense?
`A. Yes.
`
`…Q
`
`. So for this example, a histogram will be formed in memory
`100 for speed for only the pixels in the box, right?
`A. So if you configure…to only allow velocity data…from the
`pixels…then the only velocities that would go into the memory
`would be the ones corresponding [to] the pixels in that box.
`
`. Once we formed the speed histogram for the pixels…in the
`XY box in the middle of Figure 2014, we have finished forming
`the histogram, is that right?
`A. If that’s when you want to finish the histograming….
`
`Exhibit 2014
`
`…Q
`
`…Q
`
`. …could we then add an additional set of pixels, say to the
`right of the box I've shown in Figure 2014…and continue
`forming the histogram in memory 100?
`A. The embodiment described‐ this embodiment described in
`'134 would allow that.
`
`Paper 15 (PO Resp.) at 28; Ex. 2011, 79:14–83:24; Paper 34 (Supp. PO Resp.) at 3–4.
`
`19
`
`
`
`Element [1c]: Lock-on Tracking Embodiment
`Illustration
`
`Step 1: A small area
`of
`interest
`(blue)
`is
`chosen within
`the
`target red circle. No
`edge (DP=1) pixels are
`processed yet.
`
`Step 2: The area of
`interest
`increases.
`Some edge pixels are
`processed.
`
`Step 3: The area of
`interest is increased and
`the center
`is moved,
`because two boundaries
`have
`already
`been
`determined (XMAX and
`YMAX).
`
`Step 4: The area of
`interest is increased and
`the center is moved. All
`boundaries have been
`determined.
`
`Paper 15 (PO Resp.) at 12–13.
`
`20
`
`
`
`Lock-on Tracking Embodiment
`
`The lock‐on tracking
`embodiment is like
`claims 58 and 63 that
`were deemed
`patentable during
`prosecution of the ’001
`patent, the parent of
`the ’134 patent.
`
`The lock‐on tracking
`embodiment is also like
`claims 1‐6 of the ’134
`patent.
`
`Paper 15 (PO Resp.) at 10–11; Paper 34 (Supp. PO Resp.) at 4‐5.
`
`21
`
`
`
`Phillips Interpretation of Claim Element [1c]
`
`• Claim language
`
`• Specification
`
`
`
`
`
`• Prosecution History
`
`Paper 15 (PO Resp.) at 19; Paper 34 (Supp. PO Resp.) at 2.
`
`22
`
`
`
`Prosecution History: Hunke
`
`Claim element [1c] read as broadly as
`Samsung suggests would encompass Hunke
`(Ex. 2005) over which the claim was
`allowed during prosecution.
`
`Hunke calculates a color histogram, and
`then finds target colors based on the
`histogram (Figure 5, item 76). Color
`analysis happens after histogram
`formation.
`
`Hunke “unequivocally” defines the set of
`pixels that is the target based on analysis of
`color, motion, and other analysis if needed.
`
`Paper 15 (PO Resp.) at 18–19; Paper 34 (Supp. PO Resp.) at 6–7.
`
`23
`
`
`
`Prosecution History: Hunke
`
`Hunke’s “unequivocal” detection of the
`contiguous set of target pixels defining X
`and Y minima and maxima of the target:
`
`•
`
`•
`
`The virtual camera is “constantly
`adjusted to the position and size of the
`tracked target.”
`
`The virtual camera box is adjusted to
`leave “enough of a border that the
`object will remain within the virtual
`camera in the next video frame.”
`
`Hunke, Fig. 1 (tracking
`module and virtual box)
`
`Paper 34 (Supp. PO Resp.) at 6–7; Ex. 2005 (Hunke), 7:1–5, 12:29–30.
`
`24
`
`
`
`’134 Patent Prosecution History
`
`The applicant amended claim 1 to add [1c] overcome Hunke
`(Ex. 2005):
`
`[1a] forming at least one histogram of the pixels in the one or
`more of a plurality of classes in the one or more of a
`plurality of domains, said at least one histogram referring
`to classes defining said target[[,]]; and
`[1b] identifying the target [[form]]in said at least one
`histogram itself,
`[1c] wherein forming the at least one histogram further
`comprises determining X minima and maxima and Y
`minima and maxima of boundaries of the target.
`
`Paper 15 (PO Resp.) at 18–21; Paper 34 (Supp. PO Resp.) at 5.
`
`25
`
`
`
`Prosecution History
`
`Claim element [1c] read as
`broadly as Samsung suggests
`would also encompass Hunke (Ex.
`2005) in combination with Grove
`(Ex. 2006).
`
`The Examiner rejected proposed
`claims of the ’001 patent (parent
`to the ’134 patent) over this prior
`art combination.
`
`Hunke
`
`Grove, p.3
`
`Paper 15 (PO Resp.) at 16–17; Paper 34 (Supp. PO Resp.) at 7.
`
`26
`
`
`
`Prosecution History
`
`The Examiner issued an
`obviousness rejection based on
`the combination of Hunke with
`Grove.
`
`The Examiner relied on page 3 of
`Grove as teaching identifying the
`target in the histogram itself.
`
`Page 3 of Grove also shows a
`tracking box centered on and
`drawn around the target.
`
`Paper 15 (PO Resp.) at 16–17; Paper 34 (Supp. PO Resp.) at 7.
`
`27
`
`
`
`’001 Patent Prosecution History
`
`The Examiner stated Claims 55, 56 were allowable over Hunke
`(rejected claims 51, 52 shown for context):
`51. [Identical claim language as ’134 Pat. 1[pre], 1[a]]…
`identifying the target from said at least one histogram.
`52. [claim 51] further comprising drawing a tracking box
`around the target.
`55. [claim 51] wherein forming the at least one histogram
`further comprises successively increasing the size of a
`selected area until the boundary of the target is found.
`56. [claim 52] wherein forming the at least one histogram
`further comprises determining X minima and maxima
`and Y minima and maxima of boundaries of the target.
`
`Paper 15 (PO Resp.) at 14; Paper 34 (Supp. PO Resp.) at 5–6.
`
`28
`
`
`
`’001 Patent Prosecution History
`
`The Examiner rejected claims 57 and 59.
`The Examiner found allowable claims 58, 63 over Hunke and Grove:
`
`57. [Identical claim language as ’134 Pat., 1[pre], 1[a], 1[b].]
`58. [claim 57] wherein identifying the target in said at least
`one histogram further comprises determining a center of
`the target to be between X and Y minima and maxima of
`the target.
`59. [claim 57] wherein identifying the target in said at least
`one histogram further comprises determining the center of
`the target at regular intervals.
`63. [claim 57] wherein forming the at least one histogram
`further comprises successively increasing the size of a
`selected area until the boundary of the target is found.
`
`Paper 15 (PO Resp.) at 14; Paper 34 (Supp. PO Resp.) at 8.
`
`29
`
`
`
`Phillips Interpretation of Claim Element [1c]
`
`• Claim language
`
`• Specification
`
`• Prosecution History
`
`
`
`
`
`
`
`Paper 15 (PO Resp.) at 19; Paper 34 (Supp. PO Resp.) at 2.
`
`30
`
`
`
`Gilbert (Ex. 1005)
`
`Intensity histograms
`are used to binarize
`the image into target
`/ non‐target pixels.
`
`Projection histograms
`of the binarized
`pixels are formed and
`then analyzed to
`determine target
`characteristics.
`
`Paper 15 (PO Resp.) at 43–45.
`
`31
`
`
`
`Gilbert (Ex. 1005)
`
`Histogram analysis to determine target characteristics:
`
`Center of area for two
`halves of the target are
`calculated rather than
`determining end points.
`
`To analyze shape, the projection
`histogram is divided into
`rectangles. The first and last
`rectangles are not used due to
`noise.
`
`Paper 15 (PO Resp.) at 44–46.
`
`32
`
`
`
`Target Boundary ≠ Histogram Limits
`
`As Dr. Hart explained, the endpoints of a projection histogram
`are not the same thing as boundaries of the target.
`
`Q. So the X MIN and MAX of the projection histogram
`need to not be the same as the X MIN and MAX of the
`target?
`THE WITNESS: So Element I C says “the X minima and
`maxima and Y minima and maxima of boundaries of
`the target," that in some cases will be the MIN and
`MAX histogram statistics that we saw but in some cases
`it won't be.
`Q. Right. So the MIN and MAX of a projection
`histogram and the MIN and MAX of a target boundary
`are different things?
`THE WITNESS: That's what's shown in Figure 17. . . .
`
`Paper 15 (PO Resp.) at 26 n.9; Ex. 2011, 68:9–23.
`
`33
`
`
`
`Hashima (Ex. 1006)
`
`Hashima detects a pre‐defined
`target mark.
`
`Hashima was of record during
`prosecution of the ’134
`patent.
`
`Paper 15 (PO Resp.) at 46–51, 60.
`
`34
`
`
`
`Hashima (Ex. 1006)
`
`Hashima binarizes the image,
`and then analyzes the
`resultant shapes to find the
`target mark.
`
`Object size is used to screen
`potential targets.
`
`Paper 15 (PO Resp.) at 46–51, 60.
`
`35
`
`
`
`Hashima (Ex. 1006)
`
`A projection histogram is used
`to count peaks and valleys to
`find the target.
`
`Peaks and valleys, not target
`boundaries, are determined to
`find the target.
`
`Paper 15 (PO Resp.) at 46–51, 60.
`
`36
`
`
`
`Hashima (Ex. 1006)
`
`The “opposite end points”
`are used in post‐
`histogram‐formation
`analysis.
`
`The goal is to determine
`center points, not target
`boundaries.
`
`Paper 15 (PO Resp.) at 46–51, 60.
`
`37
`
`
`
`Hashima (Ex. 1006)
`
`The target window is
`sized after the
`histogram is formed,
`using the center and X,
`Y length of the object
`to size the window.
`
`Hashima Figure 23
`
`Paper 15 (PO Resp.) at 51–52; Paper 34 (Supp. PO Resp.) at 6, Ex. 1006 (Hashima), 14:4–12.
`
`38
`
`
`
`Hashima (Ex. 1006)
`
`The target window is
`sized after the
`histogram is formed,
`using the center and X,
`Y length of the object
`to size the window.
`
`Paper 15 (PO Resp.) at 51–52; Paper 34 (Supp. PO Resp.) at 6, Ex. 1006 (Hashima), 14:4–12.
`
`39
`
`
`
`Hashima (Ex. 1006)
`
`Adjustment of the target
`window is for the next
`frame, not the current
`frame.
`
`Paper 8 (Preliminary PO Resp.) at 34; Paper 34 (Supp. PO Resp.) at 6; Ex. 1005, 5:66–67.
`
`40
`
`
`
`Gerhardt (Ex. 1013)
`
`Gerhardt discloses a video camera on a helmet that
`captures image frames, and a claimed improved way
`to identify and track the user’s pupil.
`
`Paper 15 (PO Resp.) at 66‐67.
`
`41
`
`
`
`Gerhardt (Ex. 1013)
`
`The intensity histogram
`of Gerhardt is not used
`to find target
`boundaries.
`
`The histogram is used to
`find an intensity
`threshold (Fig. 5, item
`80). The result of the
`histogram is then used
`to binarize the image.
`
`Paper 15 (PO Resp.) at 56; Paper 34 (Supp. PO Resp.) at 6.
`
`42
`
`
`
`Gerhardt (Ex. 1013)
`
`The pixel grouping
`process does not use a
`histogram.
`
`The pixel selection and
`region growing process
`happens after the
`histogram is formed.
`
`Paper 15 (PO Resp.) at 40, 56; Paper 34 (Supp. PO Resp.) at 6; Ex. 1013, 12:51‐61.
`
`43
`
`
`
`Gerhardt (Ex. 1013)
`
`Once blobs have been
`formed, Gerhardt
`selects the pupil from
`among the blobs based
`on properties such as
`area and length‐to‐
`width ratio.
`
`Paper 15 (PO Resp.) at 40, 56; Paper 34 (Supp. PO Resp.) at 6; Ex. 1013, 13:3‐22.
`
`44
`
`
`
`Bassman (Ex. 1014)
`
`Bassman monitors
`traffic in a multi‐lane
`road.
`
`Bassman forms a 1D
`Strip based on pixels in
`a lane.
`
`The pixels in the lane
`are classified as
`“background” or
`“detection” pixels.
`
`Paper 15 (PO Resp.) at 41–42.
`
`45
`
`
`
`Bassman (Ex. 1014)
`
`A histogram of each
`horizontal line of pixels in
`the strip is formed to
`classify each vertical strip
`pixel.
`
`The attributes of the
`histogram are analyzed to
`classify the lane pixels.
`
`Subsequent analysis is
`needed to find vehicle
`boundaries.
`
`Paper 15 (PO Resp.) at 41–42, 56.
`
`46
`
`
`
`Bassman (Ex. 1014)
`
`A “vehicle hypothesis
`generator” is used to
`determine which strip
`pixels represent a vehicle.
`
`Paper 15 (PO Resp.) at 41–42, 56 ;Ex. 1014, 7:18–42.
`
`47
`
`
`
`CERTIFICATE OF SERVICE
`
`Pursuant to 37 C.F.R. § 42.6(e), the undersigned certifies that on June 25, 2018, the
`foregoing PATENT OWNER IMAGE PROCESSING TECHNOLOGIES
`LLC’S DEMONSTRATIVES was served via electronic mail upon the following
`counsel of record for the Petitioner:
`
`
`John Kappos (Reg. No. 37,861)
`jkappos@omm.com
`
`Marc J. Pensabene (Reg. No. 37,416)
`mpensabene@omm.com
`
`Nicholas J. Whilt (Reg. No. 72,081)
`nwhilt@omm.com
`
`Brian M. Cook (Reg. No. 59,356)
`bcook@omm.com
`
`Clarence Rowland (Reg. No. 73,775)
`crowland@omm.com
`
`IPTSAMSUNGOMM@OMM.COM
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`/s/ Chris J. Coulson
`Chris J. Coulson (Reg. No. 61,771)
`BUNSOW DE MORY LLP
`101 Brambach Rd.
`Scarsdale, NY 10583
`Tel.: (646) 502-6973
`ccoulson@bdiplaw.com
`
`
`
`
Accessing this document will incur an additional charge of $.
After purchase, you can access this document again without charge.
Accept $ Charge
Still Working On It
This document is taking longer than usual to download. This can happen if we need to contact the court directly to obtain the document and their servers are running slowly.
Give it another minute or two to complete, and then try the refresh button.
A few More Minutes ... Still Working
It can take up to 5 minutes for us to download a document if the court servers are running slowly.
Thank you for your continued patience.
This document could not be displayed.
We could not find this document within its docket. Please go back to the docket page and check the link. If that does not work, go back to the docket and refresh it to pull the newest information.
Your account does not support viewing this document.
You need a Paid Account to view this document. Click here to change your account type.
Your account does not support viewing this document.
Set your membership
status to view this document.
With a Docket Alarm membership, you'll
get a whole lot more, including:
- Up-to-date information for this case.
- Email alerts whenever there is an update.
- Full text search for other cases.
- Get email alerts whenever a new case matches your search.
One Moment Please
The filing “” is large (MB) and is being downloaded.
Please refresh this page in a few minutes to see if the filing has been downloaded. The filing will also be emailed to you when the download completes.
Your document is on its way!
If you do not receive the document in five minutes, contact support at support@docketalarm.com.
Sealed Document
We are unable to display this document, it may be under a court ordered seal.
If you have proper credentials to access the file, you may proceed directly to the court's system using your government issued username and password.
Access Government Site
