Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
CA 02694123 2010-02-22
Description
FIELD OF THE INVENTION
This application pertains to a method for capturing the 3D motions of an
actor(s) with optical motion capture
sensors which do not need to be rigidly mounted relative to each other or
relative to any part of the acting
space. This is achieved by determining the position and orientation of a
sensor relative to said acting space
substantially instantly, without disrupting the motion capture session or
introducing obstacle to the acting
space. By applying this invention to all said sensors, a multi-sensor optical
motion capture system can be
easily set up to capture actor motions from different directions and locations
without having to go through
any dedicated calibration procedure or having to rigidly mount said sensors
relative to the acting space.
BACKGROUND OF THE INVENTION
Optical 3D motion capture ("mocap") systems have been in use for several
decades. For example, to
improve a rehabilitation procedure, a patient's motions must be captured for
analysis and correlation with the
results. To improve the performance of a sportsperson, his or her motions need
to be compared with those
of the champion in order to determine the differences. Games, cartoons and
movies require lots of computer
animation to produce, the motions seen in the animation can be acted out by
actors, digitized by motion
capture systems, then applied to drive otherwise motionless computer
characters. Recently virtual reality
has become a popular research topic because the technology can be applied for
virtual training of pilots,
surgeons, athletes and all kinds of special people. To achieve the training
goal the training subject
("immersant") must first be made to immerse in a virtual environment. The
virtual environment must react to
the motions of the immersant, and the immersant's motions can be sensed with a
motion capture system.
A multi-sensor optical 3D motion capture system available today is made with
either 2D sensing units or 3D
sensing units ("sensors"). A system with 2D sensors requires at least two
sensing units in order to sense 3D
motions of an object. Such systems are being marketed by at least Vicon Motion
Systems of UK, Motion
Analysis Corporation and Phase Space Inc. of USA, and Qualisys AB of Sweden. A
system with 3D sensors
requires just one sensing unit to sense 3D motions. Such systems are being
marketed by at least Northern
Digital Inc. and Phoenix Technologies Inc. of Canada.
Previously, when a 3D motion capture system consists of two or more sensors,
the relative positions and
orientations between said sensors must be precisely known in order for the
system to fuse the multiple sets
of data produced by the sensors into a single set representing the unique
motions of the object being
captured. The process of finding out said relative positions and orientations
is referred to as multi-sensor
system calibration ("system calibration"). This process invariably requires
said sensors to simultaneously
collect corresponding position data of markers defining a plurality of points
in 3D space. Until recently every
optical motion capture system in the market has resorted to using a rigid tool
("calibration tool") to carry the
markers and requiring the user to manually wave it over the intended capture
space in 3D to collect said
corresponding position data ("calibration data"). For a system made with 2D
sensors, the relative positions
between said markers must be precisely known, hence a rigid precision tool is
required to carry the markers.
Said marker data must also be spread over a 3D space, hence said precision
tool must be at least 2D in
construction. To calibrate such a system accurately requires the user to
understand somewhat how
calibration is accomplished and how the tool should be waved to collect the
necessary data. For a system
composed of 3D sensors, said tool can be simpler in construction, such as a
stick, and carries fewer
markers. However, it still requires the user to understand, though in lesser
degree, how calibration is
accomplished and how the simpler calibration data must be collected. This
procedure must be repeated
every time when a sensor is or suspected to have been moved relative to the
other sensors.
In 2006, Phoenix Technologies Inc. of Canada ("PTI") improved its 3D sensor
system calibration process by
making use of the marker data captured during a motion capture session. This
eliminated the need to collect
calibration data in a separate manual procedure and the need to have a
calibration tool, thus making its
Visualeyez system the first optical 3D motion capture system with fully
automatic system calibration
capability. Moreover, PTI programmed its system to continuously update the
calibration data, thus made the
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system calibration adaptive ("adaptive calibration") to sensor movements and
setup changes due to factors
such as temperature variation.
Nevertheless the PTI adaptive calibration capability still requires the system
to collect a large amount of
marker data before the system can be calibrated to high enough accuracy. This
makes the system
calibration tolerant of slow setup changes only, such as those due to slow
room temperature variations. In
case the system setup suffered a sudden change, the system may yield
inaccurate motion capture data for a
significant duration during and after the change. If the setup experiences a
continuous movement, the
system may even stay inaccurate for as long as the movement last. This makes
said automatic adaptive
calibration capability still not good enough for situations in which the
sensors may keep moving during a
motion capture session, such as when they are mounted on a flexible structure
or on a moving platform.
It is obvious that one way to make every captured motion data set ("mocap
data") accurate is to keep the
system calibrated at all times. This means that in case the system setup
suffers a sudden change, the
system must recover its accurate calibration instantly, with just one new set
of motion data captured after the
change if possible.
The present invention not only eliminates the need for the user to manually
collect calibration data in a
separate procedure, but also enables a multi-sensor optical 3D motion capture
system composed of 3D
sensors to be calibrated instantly while the sensors may be in constant random
motion.
SUMMARY OF THE INVENTION
The present invention provides a method for instantly calibrating a multi-
sensor optical 3D motion capture
system composed of 3D sensors. Said method consists three or more reference
markers and an algorithm.
The reference markers are attached rigidly relative to the motion capture data
coordinate reference frame
("world CRF", or "WCRF"), are arranged such that at least three are seen by
each sensor of the system
substantially at all times, and are pre-calibrated such that their relative
positions to each other are precisely
known. The algorithm inverts the matrix of reference marker data in the WCRF,
multiplies the inverse with
the matrix of reference marker data obtained by a sensor in that sensor's
local coordinate reference frame
("sensor CRF", or "SCRF"), and directly uses the product to compute positions
of the motion capture
markers seen by that sensor in the WCRF, while said sensor may be moving
randomly. In one exemplary
embodiment of the method which avoids introducing obstruction to the motion
capture space, all reference
markers are located substantially on one plane (such as the floor), the
algorithm artificially adds at least one
cross-product of the reference marker data to make the matrix invertible, and
computes the motion capture
marker positions.
The invention further provides a method for automatically pre-calibrating the
relative positions of the
reference markers by using the 3D sensors of the system itself without
purposefully manipulating any of
them. Said method consists arranging the three or more reference markers
attached rigidly to the WCRF
such that at least three are seen by each sensor of the system substantially
at all times, and at least three
seen by a first sensor of the system are also seen by at least one second
sensor of the system. At least
three reference markers seen by a second sensor of the system are also seen by
at least one third sensor of
the system, and so on, such that at least three reference markers seen by a
last sensor of the system are
also seen by at least one second last sensor of the system.
DETAILED DESCRIPTION OF THE INVENTION
Prior Art
To the best knowledge of this inventor, there is no prior art relating to
instant calibration of a multi-sensor
optical 3D motion capture system, whether the system is made of 2D sensors or
3D sensors. The closest
technology for multi-sensor optical 3D motion capture system calibration,
developed by Phoenix
Technologies Inc. of Canada for their Visualeyez system, is only capable of
automatic calibration which
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requires the use of numerous previous sensed data and hence cannot achieve
instant calibration or tolerate
continuous sensor motions. All other known multi-sensor optical 3D motion
capture systems require the user
to manually help the system collect a vast amount of data for calibration,
which means they cannot tolerate
any sensor movement at all during the entire motion capture session. Any
sensor movement during a motion
capture session will make the system lose accuracy and require another manual
calibration procedure
before accurate motion capture can resume.
The Invention - Introduction
A fundamental object of the invention is to provide a method for instantly
calibrating a multi-sensor optical
3D motion capture system so that the system may tolerate some possible
constant random sensor
movements during a motion capture ("mocap") session without losing accuracy.
Another object of the
invention is to achieve the instant calibration capability without introducing
obstruction into the motion
capture space ("mocap space").
Below first describes a general method for achieving the instant calibration
object of the invention. However
this general method requires the use of at least four reference markers which
must be located in a 3D
pattern and fixed relative to the motion capture space. This would introduce
obstruction to a typical mocap
space which is normally simply an empty space over a flat floor on which the
motion capture subject(s)
("mocap subject") or actors act out their motions. To eliminate the possible
obstruction, a preferred
embodiment of the invention is further described subsequently.
General Embodiment with Pre-Calibrated Reference Markers
FIG. 1 illustrates a general embodiment of the present invention. S1, Sd, Se
denote three of the possibly
many more 3D sensors of a multi-sensor optical 3D motion capture system. The
numerous r(.)'s denote
reference markers located within the motion capture space fixed relative to
the motion capture data
coordinate reference frame WCRF. It is assumed that sensor Sd is able to sense
n+1 of the reference
markers r(0), r(1), ..., r(n) and h motion capture markers ("mocap markers")
c(1), c(2), ..., c(h) on the mocap
subject at time t.
Let p(Ow), p(1w), ..., p(nw) denote the 3x1 position vectors ("positions") of
the reference markers r(0),
r(1), ..., r(n) in the WCRF ("world positions"). It is assumed in this
embodiment of the invention that they are
accurately known by a pre-calibration procedure. Let p(Os,t), p(Os,t), ...,
p(ns,t) denote the positions of the
same reference markers as sensed by sensor Sd at time tin the sensor's local
coordinate reference frame
SCRF ("local positions"). Then it is well-known that there exists a 4x4
transformation matrix, denote by
T(ws,t), such that
T(ws,t) [(iw)] = [Pist]) fori=0, 1, ..., n, (1)
T(ws,t) p(Ow) p(lw) ... p(nw) _ p(Os,t) p(ls,t) ... p(ns,t) (2)
1 1 ... 1 1 1 ... 1 11
r(0), r(1), ..., r(n) := reference markers seen by sensor Sd,
c(1), c(2), ..., c(h) := motion capture markers seen by sensor Sd,
where T(ws,t) is composed of a 3x3 matrix representing rotation between the
WCRF and the SCRF at time t,
denote it by R(ws,t), and a 3x1 vector representing position offset between
origins of the WCRF and SCRF
at time t, denote it by O(ws,t), in the format
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R(ws,t) O(ws,t)
T(ws,t) _ (3)
0 1 11
R(ws,t) := 3x3 rotation matrix between WCRF and SCRF at time t,
O(ws,t) := 3x1 position offset between origins of the WCRF and SCRF at time t.
Similarly, let p(clw,t), p(c2w,t), ..., p(chw,t) denote positions of the h
mocap markers c(1), c(2), ..., c(h) on
the mocap subject at time tin the WCRF. Let p(cls,t), p(c2s,t), ..., p(chs,t)
denote positions of the mocap
markers at time t as sensed directly by the sensor in the SCRF. Then
T(ws, t) p(c1w, t) p(c2w,t) ... p(chw, t) _ p(c1s, t) p(c2s,t) ... p(chs, t)
(4)
1 1 ... 1 1 1 ... 1
Note that if T(ws,t) can be derived, then the mocap marker positions,
p(ciw,t), p(c2w,t), ..., p(chw,tcan be
computed, which is the fundamental objective of every motion capture system in
the market.
To derive the transformation matrix T(ws,t) we must first derive the rotation
matrix R(ws,t) and the offset
vector O(ws,t). To do this, first substitute (3) into (1) to get
R(ws,t) p(iw) + O(ws,t) = p(is,t), for i = 0, 1, ..., n. (5)
Subtracting (5) for one value of the variable i from the same with another
value of i results in
R(ws,t) (p(iw) - paw)) = (p(is,t) - p(js,t)), i, j = any of 0, 1, ..., n, and
R(ws,t) [p(Ow) - p(j(O)w) ... p(nw) - p(j(n)w)]=
[p(Os, t) - p(j(O)s, t) ... p(ns, t) - p(j(n)s, t)],
j(.) = any one of 0, 1, ..., n, and each needs not be distinct. (6)
Denote the large matrices as
P(/jw) [p(Ow) - p(j(O)w) ... p(nw) - p(j(n)w)],
P(/js,t) [p(Os,t) - p(j(0)s,t) ... p(ns, t) - p(j(n)s, t)], j(.) = any one of
0, 1, ..., n,
then (6) can be simply expressed as
R(ws,t) P(/jw) = P(/js,t). (7)
From (7) it is obvious that if P(/jw) is full-rank, 3, then it can be inverted
for computing R(ws,t) as
R(ws, t) = P(/is, t) P(Ijw)' (P(/jw) P(/jw)) -' , (8)
and from (5) O(ws,t) can be computed as
O(ws,t) = p(is,t) - R(ws,t) p(iw), for i = any one of 0, 1, ..., n. (9)
With T(ws,t) computable according to (8), (9) and (3), note now that the
ultimate purpose of a motion capture
system is to obtain the h sensed motion capture marker positions in the WCRF,
p(clw,t), p(c2w,t), ...,
p(chw,t). Towards this end, note that (4) implies
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R(ws,t) p(cgw,t) + O(ws,t) = p(cgs,t), for g= 1, 2, ..., h. (10)
Plugging (9) into (10) yields
R(ws,t) (p(cgw,t) - p(iw)) = p(cgs,t) - p(is,t),
and therefore
p(cgw,t) = R(ws,t) -' (p(cgs,t) - p(is,t)) + p(iw), for g =1, 2, ..., h, i =
any one of 0, 1, ..., n, (11)
= (Pow) P(/jw)) (P(/js, t) P(ew)) -' (p(cgs, t) - p(is, t)) + p(iw). (12)
Note that all values on the right side of (12) are either known from a
reference markers pre-calibration
procedure or sensed by sensor Sd at time t only. Therefore this solution is
equivalent to the sensor position
and orientation relative to the WCRF having been calibrated instantly, hence
insensitive to sensor
movements. The full-rank requirement of P(/jw) can be satisfied easily if the
number, n+1, of reference
markers seen by the sensor is 4 or more (n23) and they are located in a 3D
pattern.
Preferred Embodiment with Reference Markers on a Plane
Having to locate the reference markers in a 3D pattern within the sensing
space of a sensor means that at
least some may protrude into the mocap space, unless they are all fixed at the
edges of the capture space
such as the bottom ("floor"), the top ("ceiling"), and/or the sides ("walls").
Markers placed far away from the
mocap subject are generally inaccurate to sense, which is why the mocap
subject does not make use of
those places for acting in the first place. Therefore the ceiling and walls of
a mocap space on earth are
generally not good for locating the reference markers for instant system
calibration purpose. Having some
reference markers protruding into the middle of the mocap space is also not
good since this would restrict
utility of the space. This leaves only the floor a relatively acceptable and
practical place for locating the
reference markers for instant system calibration, as illustrated by FIG. 2.
Assuming as before that sensor Sd is able to sense n+1 of the reference
markers r(0), r(1), ..., r(n) and h
motion capture markers c(1), c(2), ..., c(h) on the mocap subject at time t,
except that all n+1 reference
markers are now fixed on the mocap floor as shown in FIG. 2. Since the floor
is substantially a plane, the
difference vectors p(iw) - p(j(i)w), ..., p(nw) - p(/(n)w) in P(/jw) of (7),
which all lie in the plane, are linearly
dependent on each other. Hence P(/jw) as defined in (7) cannot be full-rank
and therefore is not invertible
when the reference markers are all fixed on the floor.
To make P(/jw) full-rank, one way is to artificially introduce another vector
which is neither on nor parallel to
the same plane to P(/jw). A cross-product is guaranteed to be such a vector.
Hence let's introduce at least
one cross-product of two linearly independent members of the aforementioned
difference vectors. This
yields a new P(/jw) for this embodiment of the invention as
P(/jw) [p(Ow) - p(j(O)w) ... P(nw) - p(j(n)w) (p(kw) - P(j(k)w)) x (P(lw) -
p(j(l)w))]= (13)
Of course this means the corresponding cross-product(s) must also be
artificially introduced to P(/js,t) in
accordance to (6). This changes P(/js,t) for the case when all reference
markers are on one plane to
become
POs, t) :_
[p(Os,t)- p(j(0)s,t) ... p(ns,t)- p(j(n)s,t) (p(ks,t)- p(j(k)s,t))x(p(ls,t)-
p(j(l)s,t))]. (14)
Since a cross-product of two vectors is perpendicular to both vectors, adding
a cross-product is equivalent to
having another reference marker fixed off the floor, except this one is non-
physical and so not obstructive to
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a mocap session. This makes both P(/jw) and P(/js,t) full-rank. Hence R(ws,t)
and O(ws,t) can again be
formulated as (8), (9) respectively, and the h sensed motion capture marker
positions in the WCRF can be
computed as indicated by (12).
Now, note that since only three vectors are needed to make the three-row
P(/jw) full-rank, P(/jw) only needs
to contain two difference vectors and their cross-product to become full-rank.
Therefore, only three or more
(na2) reference markers fixed on the motion capture floor and visible to
sensor Sd are required to instantly
calibrate Sd so that it can help to capture the visible mocap marker positions
accurately.
During a mocap session the mocap subject may occlude some of the reference
markers. So depending on
how and where they are installed on the floor, in practice more than three
reference markers are likely
required to make sure that at least three will be visible to a sensor at all
times for instant calibration. For a
multi-sensor system, even more reference markers should be installed in order
for at least three to be
sensed by each sensor at substantially all times for instant calibration of
the entire system. On the other
hand, in case more than three reference markers are visible to a sensor, the
user may choose to make use
of the position data of either just three of them for fast instant
calibration, or all of them for higher calibration
precision.
Embodiment with Reference Marker Calibration
Both the general embodiment and preferred embodiment of this invention assumed
that the reference
marker positions in WCRF are known by a pre-calibration procedure. This
procedure can be done with either
a third-party 3D coordinate measurement machine ("CMM") or the 3D sensors of
the mocap system itself.
Note that once the reference marker positions in WCRF are known, there is no
need for the mocap system
sensor sensing spaces of the present invention to overlap to achieve system
calibration. This is exceptional
compared to all existing optical motion capture systems.
A CMM is generally meant for mechanically measuring the position of one
spatial point at a time at very high
accuracy. It is normally not available to a motion capture user, and may be
quite difficult to measure the
center position of a point light source with. An optical mocap system sensor
is normally meant for measuring
the positions of multiple markers over a large space at one time, so its
accuracy is normally lower than that
of a CMM. However a mocap system sensor is much easier to use for calibrating
the reference marker
positions with, since it is meant exactly for sensing the positions of such
markers.
To calibrate the reference marker positions using the mocap system itself, the
user can either manipulate
one of the 3D sensors to make the measurements before reusing it as part of
the mocap system, or simply
arrange the reference markers such that the system sensors can calibrate their
positions automatically.
Besides autonomy, the latter solution would have the additional advantage of
being able to tolerate slow
changes of the reference marker positions too.
To be able to calibrate the reference marker positions autonomously, one way
is to construct the system as
follows:
C1. Define the WCRF with three fixed reference markers, for example r(000) at
the origin, r(x00)
somewhere along the +x axis, and r(xyO) somewhere on the +y half of the z=0
plane. If this is not
good for a particular application, then r(000), r(x00) and r(xyO) can be
markers placed temporarily for
defining the WCRF before removal.
C2. Arrange the reference markers such that at least three will be seen by
each sensor of the system
substantially at all times during motion capture so that instant system
calibration can be achieved as
described in the previous embodiments.
C3. Further arrange the reference markers such that at least before the start
of a mocap session at least
three reference markers seen by a first sensor of the system are also seen by
at least one second
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sensor of the system. At least three reference markers seen by a second sensor
of the system are
also seen by at least one third sensor of the system, and so on, such that at
least three reference
markers seen by a last sensor of the system are also seen by at least one
second last sensor of the
system. In other words, the sensors are linked together through sharing
reference markers, and
each link is at least three markers strong.
FIG. 3 illustrates a system constructed as above. Sensors S1, Se share
reference markers r(xOO), r(1), r(2),
r(3), and sensors Se, Sd share reference markers r(3), r(4), r(5), so all
three sensors of the system are
linked together by sharing reference markers. The link between S1 and Se is
four markers strong, while the
link between Se and Sd is three reference markers strong.
To calibrate the reference marker positions, note first that since S1 can
sense the distances between
markers r(000), r(x00) and r(xy0) precisely, their world positions are
immediately calibrated. Since the world
positions of three reference markers are now available, the world positions of
the other reference markers
seen by S1, r(1), r(2), r(3) in FIG. 3 for example, can be computed according
to the preferred embodiment of
this invention. Since reference markers r(x00), r(1), r(2), r(3) are all seen
by Se too, and their world positions
are now available, the world positions of the other reference markers seen by
Se, r(4), r(5) in FIG. 3, can
also be computed now. Thus the process can continue with the other sensors and
the extra reference
markers that they see, until all reference marker world positions are
precisely calibrated. This whole process
should take just a fraction of a second. After this the mocap system becomes
able to achieve instant
calibration, and a motion capture session can start.
Practical Issues
As indicated in equation (6), the subtrahends of the difference vectors in
P(/jw) and P(/js,t) need not be
distinct. To use the same subtrahend for all the difference vectors would
actually make the algorithm easier
to implement. However, since the magnitude of a difference vector does affect
the accuracy of the inversion
in (8), it may be desirable to use different subtrahends to compute the
difference vectors in order to
maximize accuracy of the inversion. In general, it is good for accuracy to
make the magnitudes of all the
difference vectors in P(/jw) and P(/js,t) roughly the same. This can be
achieved by always using the farthest
marker position to compute each difference vector.
During motion capture, a sensor may at times not be able to see even three
reference markers. In that case
the user can assume that R(ws,t) did not change, and compute the p(cgw,t)
according to (12) using the p(is,t)
and p(iw) of a visible reference marker.
Equation (12) indicates that the world position of a mocap marker can be
computed using the world position
p(iw) and local position p(is,t) of any of the visible reference markers. This
means as many position values
as the number of visible markers can be computed for each mocap marker at any
time. By computing all of
these values then averaging them can improve accuracy of the computed world
position of each mocap
marker.
As will be apparent to those skilled in the art in light of the foregoing
disclosure, many alterations and
modifications are possible in the practice of this invention without departing
from the spirit or scope thereof.
For example, three or more reference markers may be mounted on a light rigid
structure such as a stick
frame or a portable movie camera to define the WCRF for instant calibration
purpose while a multi-sensor
mocap system is carried by a truck to capture motions of subjects acting over
an unconfined space with the
planar WCRF defining structure hovering around the mocap subject. The
reference markers may still be on
a plane, but not on the floor of the mocap space in this case. Also the
movement problems for which the
instant calibration method of this invention was developed to overcome may not
come only from the sensors,
but instead may also come from movement of the WCRF defining structure itself.
Accordingly, the scope of
the invention is to be construed in accordance with the substance defined by
the following claims.
