Projected Light Displays Using Visual Feedback

Projected Light Displays Using Visual Feedback
Projected Light Displays Using Visual Feedback
James M. Rehg1 , Matthew Flagg1 , Tat-Jen Cham2 , Rahul Sukthankar3 , Gita Sukthankar3
College of Computing
School of Computer Engineering
Cambridge Research Lab
Georgia Institute of Technology Nanyang Technological University
HP Labs
Atlanta, GA 30332
Singapore 639798
Cambridge, MA 02142
[email protected]
{Rahul,Gita}[email protected]
A system of coordinated projectors and cameras enables the
creation of projected light displays that are robust to environmental disturbances. This paper describes approaches for
tackling both geometric and photometric aspects of the problem: (1) the projected image remains stable even when the
system components (projector, camera or screen) are moved;
(2) the display automatically removes shadows caused by
users moving between a projector and the screen, while simultaneously suppressing projected light on the user. The
former can be accomplished without knowing the positions
of the system components. The latter can be achieved without direct observation of the occluder. We demonstrate that
the system responds quickly to environmental disturbances
and achieves low steady-state errors.
The increasing affordability and portability of high quality projectors has generated a surge of interest in projectorcamera systems. Recent examples include the construction of
seamless multi-projector video walls [16, 5, 7, 14], real-time
range scanning [4] and immersive 3-D virtual environment
generation [10]. In most of these previous systems, cameras
are used to coordinate the aggregation of multiple projectors
into a single, large projected display. In constructing a video
wall, for example, the geometric alignment and photometric blending of overlapping projector outputs can be accomplished by using a camera to measure the keystone distortions
in projected test patterns and then appropriately pre-warping
the projected images. The result is a highly scalable display
system, in contrast to fixed format displays such as plasma
In addition to their utility in creating wall-sized displays,
projector-camera systems can also be used to create ubiquitous, interactive displays using the ordinary visible surfaces
in a person’s environment. Displays could be conveniently
located on tabletops, nearby walls, etc. Users could reposition or resize them using simple hand gestures. Displays
could even be “attached” to objects in the environment or be
made to follow a user around as desired. This would be particularly compelling as a means to augment the output capabilities of handheld devices such as PDAs. In order to realize
this vision, two challenging sensing problems must be solved:
(1) Determining where and how to create displays based on
input from the user. (2) Creating stable displays in the presence of environmental disturbances such as occlusions by the
user and changes in ambient light.
In this paper we examine the visual sensing challenges that
arise in creating interactive occlusion-free displays using projected light in real-world environments. The first challenge is
to allow the user to interactively define the region containing
the display, and then automatically calibrate the cameras and
projectors to that region. The second challenge is to maintain the stability of the display in the face of environmental
disturbances such as occlusions. Specifically, two problems
arise in front-projection systems when a user passes between
the projectors and the display surface: (1) Shadows are cast
on the display surface due to the occlusion of one of more
projectors by the user. (2) Bright light is projected on the
user, often causing distraction and discomfort. We present
a solution to these two challenges that does not require accurate 3-D localization of projectors, cameras, or occluders,
and avoids the need for accurate photometric calibration of
the display surface. The key is a display-centric camera feedback loop that rejects disturbances and unmodelled effects.
Our system uses multiple, conventional projectors which
are positioned so that their projections overlap on the selected
display surface. It produces shadow-free displays even in the
presence of multiple, moving occluders. Furthermore, projector light cast on the occluders is suppressed without affecting the quality of the display. The result is shown in Figure 4.
The two classes of problems addressed by our system are:
(i) geometric, and (ii) photometric. The geometric problems relate to computation of the spatial correspondences between pixels in the projectors and the projected display on
the screen. The projectors should be accurately and automatically calibrated to the screen, to the camera and to each other.
The calibration should enable the images in each projector to
be pre-warped so as to create a desired projected display that
is aligned with the screen. It should be possible to control
the display area on the screen in real-time. The photometric
issues are the accurate and fast computation of the desired
pixel intensities in each projector so as to eliminate shadows
and suppress illumination on the occluder. This involves occlusion detection based on camera input and correctly adapting the projector output to achieve the necessary goals. These
two classes of problems are addressed in sections 2 and 3 respectively.
Autocalibration of Cameras and Projectors
In a multi-projector system, several projectors are positioned so that their outputs converge onto a display surface S
(see Figure 2). The goal is to combine the light from the projectors to create a single, sharp image on S. Clearly, one
cannot simply project the same raw image simultaneously
through the different projectors; not only does a given point
on S correspond to very different pixel locations in each projector, but the image produced on S from any single projector
will be distorted (since the projectors are off-center to S).
We assume that: the positions, orientations and optical parameters of the camera and projectors are unknown; camera
and projector optics can be modelled by perspective transforms; the projection screen is flat. Therefore, the various
transforms between camera, screen and projectors can all be
modelled as 2-D planar homographies:
 
p1 p2 p3
 yw  =  p4 p5 p6   Y  ,
p7 p8 p9
where (x, y) and (X, Y ) are corresponding points in two
frames of reference, and p~ = (p1 . . . p9 )T , constrained
by |~
p| = 1, are the parameters specifying the homography. These parameters can be obtained from as few as four
point correspondences, using the camera-projector calibration technique described in [13].
The homography for each camera-projector pair Tc,Pi can
be determined by projecting a rectangle from the given projector into the environment. The coordinates of the rectangle’s corners in projector coordinates (xi , yi ) are known a
priori, and the coordinates of the corners in the camera frame
(Xi , Yi ) are located using standard image processing techniques.1
Real-Time Calibration
A key issue for the robustness of the projector-camera system is the ability to recalibrate the homographies quickly if
either the camera or the projector are moved. In addition, a
basic question is how to specify the location of the display.
We now describe a real-time calibration system which addresses both of these concerns. The system uses a set of four
fiducial marks on a display surface such as a wall or table to
define the four corners of the desired projected area. Since
walls tend to be light colored, we have found that any small
dark target, such as a poker chip, can serve as a fiducial. By
positioning the targets appropriately on the display surface,
the user can identify the desired display area. Through visual
tracking of both the positions of the four markers and the corners of the quadrilateral formed by the projector output, the
appropriate transformation can be computed.
The geometric relationship between the detected corners
of the projector quadrilateral and the location of the markers determines a homography that aligns the projector output
1 Hough-transform line-fitting [1] locates the edges of the quadrilateral,
and its corner coordinates are given by intersecting these lines.
with the markers. The image coordinates of the four markers fully specify the homography between camera and screen
Tc,s . The homography between each projector and the screen
TPi ,s can be recovered using the equation:
TPi ,s = Tc,P
T ,
i c,s
where the homographies on the right hand side of the equation are all known.
In some applications the positions of the projector or camera, as well as the positions of the markers, may change over
time. We can view each of these changes as disturbances
that perturb the calibrated relationship between the cameras,
projectors, and display. In this instance, disturbance rejection can be easily accomplished by tracking the quadrilateral
corners and marker positions in real-time, and updating the
warping parameters appropriately. Note that the dynamics in
this case are extremely fast, since the only limit on the speed
at which the projector output can be changed is the overall
system bandwidth.
2.2 Experimental Results
We performed three experiments to evaluate the ability of
the visual feedback loop to compensate for disturbances to
the projector and camera positions and the positions of the
fiducial markers. Our system can perform tracking and disturbance rejection at 10 Hz.
The first experiment tested the ability of the system to
compensate for changes in the location of the markers, resulting in a resizing of the projected display. Figure 1(a) and
(b) shows the result for two different marker configurations.
Note the automatic rescaling of the display region, so that
its corners remain aligned with the markers. In each image, the boundary of the projected area is visible as a large
pale quadrilateral containing the display region. In this test
the projectors and camera remained stationary, and so the
location of the projector quadrilateral in the image does not
change (i.e. Tc,Pi did not change). These images were captured with a second camera located in the audience, which
was not used in autocalibration.
In the second experiment, we kept the camera and markers
fixed and changed the location of the projector. Small disturbances in the projector orientation can induce large changes
in the display. The result is illustrated in Figure 1(c) and (d)
for two positions of the projector. As desired, the configuration of the display region on the wall as defined by the fixed
markers is unaffected by movement of the projector. Note
also that there is no change in the marker positions between
frames, as expected (i.e. Tc,s did not change).
The third experiment tested the response of the system
when the position of the camera was changed and the projector and markers remained fixed. In this situation, there is
no change in the homography between the projector and the
display (i.e. TPi ,s does not change). However, the image locations of both the marker positions (in Tc,s ) and the quadrilateral corners (in Tc,Pi ) will change as the camera moves.
Figure 1. (a) and (b): The effect of a change in the marker configuration on the system is shown at two different time
instants. The four markers define an interface by which the user can control the size and location of the display. (c) and (d):
The effect of a change in the projector position is shown at two different time instants. The projector quadrilateral changes
while the display defined by the markers does not. (e) and (f): The effect of a change in the camera position is shown at two
different time instants. The entire image is distorted, but the display continues to fill the region defined by the markers.
Figure 1(d) and (e) illustrates the result for two camera configurations. Once again the display is unaffected, as desired.
These images where captured by the camera which is used in
Shadow Elimination and Occluder Light
In this section we describe a system which handles realtime photometric compensation using visual feedback. The
system comprises a number of projectors which are aimed at
a screen such that their projection regions overlap and a camera which is positioned such that it can view the entire screen.
During normal functioning, the system displays a high quality, dekeystoned image on the screen. When users walk between the projectors and the screen, shadows are cast on the
screen. These shadows can be classified as umbral when all
projectors are simultaneously occluded, or penumbral when
at least one projector remains unoccluded. The system eliminates all penumbral shadows cast on the screen,2 as well as
suppressing projector light falling on the occluders. This enables the system to continue presenting a high quality image
without projecting distracting light on users. See Figure 2 for
the setup.
Shadow 2
3.1 Photometric Framework
After the projectors have been geometrically aligned, we
can easily determine which source pixels from the projectors
contribute to the intensity of an arbitrary screen pixel. In the
following analysis, we assume that the contributions are at
some level additive. Given N projectors, the observed intensity Zt of a particular screen pixel at time t may be expressed
ki,t Si (Ii,t ) ,
Zt = C A +
where Ijt is the corresponding source pixel intensity set in
projector j at time t, Sj (·) is the projector to screen intensity
transfer function, A is the ambient light contribution which
is assumed to be time invariant, C(·) is the screen to camera
intensity transfer function and kjt is the visibility ratio of the
source pixel in projector j at time t. See Figure 3.
Shadow 1
full occluder
Display surface (S)
Projector 3
Camera (C)
Projector 1
Projector (P1)
Projector (P2)
Figure 2. An overhead view of the multi-projector display system. Several projectors (P1 , P2 ) are placed
such that their projection areas converge onto the display surface (S). A camera (C) is positioned so that
S is clearly visible in its field of view. The projectors combine their pre-warped outputs to create a single
high-quality image on S based on computed homographies. The system is able to dynamically compensate
for penumbral shadows and suppress projected light on
2 By definition, pixels in an umbral shadow are blocked from every projector and cannot be removed. Umbral shadows can be minimized by increasing the number of projectors and by mounting the projectors at highlyoblique angles.
Partial occluder
Projector 2
Figure 3. Photometric framework. This diagram illustrates equation (3), in which the observed display
intensity Zt is related to the combination of projector
source pixels Ijt and the corresponding visibility ratios
kjt . The visibility ratios vary accordingly with nonocclusion, partial and full occlusion.
When occluders obstruct the paths of the light rays from
some of the projectors to the screen, Zt diminishes and shadows occur. This situation is quantitatively modelled via the
visibility ratios, which represent the proportion of light rays
from corresponding source pixels in the projectors that remain unobstructed.
Mathematically, the desired intensity of a particular screen
pixel may be represented by Z0 (obtained in an initialization
phase). As an occluder is introduced in front of projector k to
create penumbral shadows, the visibility ratio kjt decreases,
such that kjt < 1. Hence Zt < Z0 . These deviations in the
screen can be detected via a pixel-wise image difference between current and reference camera images to locate shadow
Iterative Photometric Compensation
Our system handles occluders by
1. compensating for shadows on the screen by boosting the
intensities of unoccluded source pixels; and
2. removing projector light falling on the occluder by
blanking the intensities of occluded source pixels.
As in [12], the change in the intensity of each source pixel
in each projector is controlled by the alpha value associated
with the pixel:
Ijt = αjt I0 ,
where I0 is the original value of the source pixel (i.e. pixel
value in the presentation slide) and is the same across all
projectors, while αjt , 0 < αjt < 1 is the time-varying,
projector-dependent alpha value. The alpha values for the
source pixels in one projector is collectively termed the alpha
mask for the projector.
Shadows should be eliminated by adjusting the alpha
masks for all projectors such that |Zt − Z0 | is minimized.
Additionally, alpha values for occluded source pixels should
be set to zero in order to suppress projector light falling on
the occluder. This can be done iteratively with the aid of the
visual feedback from the camera.
Components of the Visual Feedback Rule
Eliminating shadows involves increasing values for corresponding source pixels. The shadow elimination (SE) component of the system is based on
(∆αjt )SE = −γ(Zt − Z0 ),
where ∆αjt = αj(t+1) − αjt is change of αjt in the next
time-frame, and γ is a proportional constant. This component
is a simple proportional control law.
Suppressing the projector light falling on the occluders involves diminishing the source pixels corresponding to the occluded light rays. We determine whether a source pixel is
occluded by determining if changes in the source pixel have
resulted in changes in the screen pixel. However, since there
are N possible changes of source pixel intensities from N
projectors but only one observable screen intensity, we need
to probe by varying the source pixels in different projectors
separately. This cyclical probing results in a serial variation
of the projector intensities.
The light suppression (LS) component of the feedback rule
is based on
(∆αjt )LS = −β
∆Zt2 + ²
where ∆Zt = Zt − Zt−N is the change in the screen pixel
intensity caused by the change of alpha value ∆αj(t−N ) in
the previous time frame when projector j is active, and β is a
small proportional constant and ² is a small positive constant
to prevent a null denominator.
The rationale for (6) is that if the change in αjt results in a
corresponding-sized change in Zt , the subsequent change in
αjt will be relatively minor (based on a small β). However if
a change in αjt does not result in a change in Zt , this implies
that the source pixel is occluded. The denominator of (6)
approaches zero and αjt is strongly reduced in the next time
frame. Hence occluded source pixels are forced to black.
Note that the system must be able to discover when a pixel
which was turned off due to the presence of an occluder is
available again, due to the occluder’s disappearance. This
requirement is smoothly incorporated into our algorithm.
The complete iterative feedback rule is obtained by combining (5) and (6) to get
∆αjt = (∆αjt )SE + (∆αjt )LS .
The alpha values are updated within limits such that
if αjt + ∆αjt > 1,
if αjt + ∆αjt < 0,
αjt =
αjt + ∆αjt , otherwise.
3.4 System Details
During the initialization phase of its operation (when the
scene is occluder-free) the system projects each presentation
slide and captures a reference image per slide with the camera. During normal operation, the system camera continuously acquires images of the projected display which may
contain uncorrected shadows. The comparison between the
observed images and the reference image facilitates the computation of the alpha masks for individual projectors through
(7). These are merged with the presentation slide in the
screen frame of reference, followed by further warping into
the projector frame of reference. These projected images
from all projectors optically blend to form the actual screen
Note that the cost of shadow elimination is the use of redundant projectors. This means that at any point in time there
are pixels on one or more projectors that are not being utilized
because they fall outside the display surface or are occluded.
We feel this is a small price to pay, particularly in comparison
to the large costs, in either expense and required space, for
other display technologies such as rear projection or plasma.
Fortunately, portable projectors are becoming increasingly
affordable as their image quality improves and their weight
Some images of the system in action are shown in Figure 4. The images demonstrate the difference between
shadow elimination alone and in combination with occluder
light suppression.
A benefit of using a visual feedback system (as opposed
to an open-loop approach based on an accurate photometric
model) is that the system is surprisingly robust. For instance,
if one of the projectors in the multi-projector array were to
fail, the remaining projectors would automatically brighten
their images to compensate. Furthermore, the overall brightness of the entire multi-projector array can be changed simply
by adjusting the camera aperture.
Figure 4. Comparison between different projection systems. These images were taken from an audience member’s viewpoint:
(a) Single projector; (b) Two aligned projectors, passive; (c) Two aligned projectors with shadow elimination only; (d) Two
aligned projectors with shadow elimination and occluder light suppression. Note that the harsh shadow in (a) is replaced
by softer double shadows in (b). Shadows are completely removed in (c) and (d). However, the user’s face is brightly
illuminated with projected light in (c). This blinding light is completely suppressed in (d).
Related Work
Research in the area of camera-assisted multi-projector
displays is becoming more popular, particularly in the context of seamless video walls [16, 8, 5, 7, 14, 10]. Two previous papers [12, 6] presented solutions to the shadow elimination problem for forward-projection systems. In more recent
unpublished work [2], we present a preliminary version of
the occluder light suppression system described in Section 3.
This problem is technically much more challenging because
it requires the ability to determine which rays of projected
light are being occluded. We believe our results in occluder
light suppression are unique.
A simple camera feedback system, related to the one presented here, was used by [14] to adjust projector illumination
for uniform blending in the overlap region of a video wall.
In [9] a projector-mirror system is used to steer the output
of a single projector to arbitrary locations in an environment.
The Shader Lamps system [11] uses multiple projectors and
a known 3-D model to synthesize interesting visual effects on
3-D objects. The geometric self-calibration techniques used
in this paper were adopted from [13], where they were applied to the task of automatic keystone correction for single
projector systems. In the Tele-graffiti system [15], a camera
is used to track the motion of a flat display surface and automatically maintain the alignment of a projected image with
the moving display. This system shares our goal of real-time
geometric compensation, but lacks interactive control of the
display window and the ability to compensate for occlusions.
In their work on the “Magic Board”, Coutaz et al. [3] describe a system in which a user can control the size of a projected display window by manipulating poker chips which
are tracked by a camera. In this work, however, the projector
and screen are carefully aligned in advance, and the detected
poker chips specify window coordinates in a pre-calibrated
and fixed reference frame. Our work extends this paradigm
to include autocalibration and the ability to adapt to changes
in the positions of the camera and projector.
Conclusions and Future Work
Visual feedback is a key component in developing robust,
interactive projected light displays. Camera-based sensing of
the environment makes it possible to compensate in real-time
for both geometric and photometric effects. Visual tracking
of both fiducial markers and the corners of the projector output supports real-time autocalibration and makes the system
robust to changes in the position of the projector, camera, and
screen. It also permits the user to specify the desired screen
location by positioning fiducial marks on the display surface.
In addition, a photometric feedback rule makes it possible to
eliminate shadows and the illumination of occluding objects
in a multi-projector configuration.
In the future, we plan to extend the system in several ways.
In addition to increasing the frame rate at which the system
operates, we will incorporate multiple cameras into the visual feedback loop. This will enable the system to work reliably even when a camera is occluded. We are also developing
user-interface techniques for controlling and adjusting virtual
displays using hand gestures. In particular, we are exploring
shadow detection as a means to support touch-based interaction with the projected light display.
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