Geometrical Picture Integration in SEMI-CAVE Virtual Reality

Dariusz Sawicki

, Łukasz Izdebski

, Agnieszka Wolska

and Mariusz Wisełka

Warsaw University of Technology, Institute of Theory of Electrical Engineering,

Measurements and Information Systems, Warsaw, Poland

Central Institute for Labour Protection - National Research Institute (CIOP-PIB), Warsaw, Poland

Keywords: Image Stitching, Multimedia, Virtual Environment, Immersive VR, CAVE.

Abstract: Virtual reality (VR) is the most fascinating multimedia solution of recent years. Cave (Cave Automatic

Virtual Environment) is the most advanced example of VR installation. The aim of the work is to present an

image stitching problem in specific cave installation. The low-budget installation called SEMI-CAVE has

been built to study the impact of visual environment on human psychophysiology at the workplace. Six

projectors display images on four walls of a relatively large room. Correct stitching of images with perfect

geometry is the deciding factor in ensuring good immersion in VR under these conditions. We have

developed a special image stitching subsystem working in the SEMI-CAVE solution. The subsystem makes

it possible to easily combine individual images to ensure the correct geometry of the displayed content. In

addition, the implementation of the stitching subsystem was carried out at the shader level, which ensured

the fastest possible technical solution. The work presents subsystem assumptions, the method of

implementation and conducted tests.

1 INTRODUCTION

1.1 Motivation

Virtual reality (VR) is one of the most attractive

computer science solutions in recent years.

Attractive not only for players of computer game

and advertising specialists, but also scientists from

many fields. Cave (Cave Automatic Virtual

Environment) is the most spectacular example of VR

installation. Cave is a solution known for many

years, but due to the costs and many technical

problems this solution is relatively rarely used.

The realization discussed here – SEMI-CAVE –

is an example of cave implementation, projected and

developed in recent years in the Central Institute for

Labour Protection - National Research Institute

(CIOP-PIB). It is one of the laboratories which were

built as a part of Tech-Safe-Bio project (TECH-

SAFE-BIO, 2015). The research plans related to the

SEMI-CAVE laboratory include interdisciplinary

study on health and safety of employees. VR

solutions will allow the researchers to study the

impact of physical environment on workers. The

laboratory was initially launched in the end of 2015.

After the first work (technical issues and calibration)

we focused on experiments with acquiring images

for preparing VR environment. The impressions of

viewers have confirmed the correctness of the

project concept – i.e. sufficient immersion into VR.

The quality of the displayed image in CAVE

installations, is a key issue determining the

correctness of immersion into the virtual reality

created inside the installation. Most often, two

aspects of this problem are discussed (Slater, 2003):

• Immersion Into The Virtual Environment.

This concept defines how well VR represents

the real world. We can list the following

parameters: correctness of stitching and image

geometry, color rendering and perception,

viewing angle, image resolution, etc.;

• Presence. An aspect relating to the perception

of virtual reality by the user. In practice, not

measurable, connected with the person using

the installations at a given moment. This

parameter depends on: the content presented

for a long time inside the installation and the

emotional state. It depends on the quality of

the immersion in VR.

The first thing SEMI-CAVE users see when

entering a room is of course the whole image

displayed on all four walls. The impression of

100

Sawicki, D., Izdebski, Ł., Wolska, A. and Wisełka, M.

Geometrical Picture Integration in SEMI-CAVE Virtual Reality.

DOI: 10.5220/0006922701000107

In Proceedings of the 2nd International Conference on Computer-Human Interaction Research and Applications (CHIRA 2018), pages 100-107

ISBN: 978-989-758-328-5

immersion is determined at this point by the

correctness of building virtual reality through

component images (displayed on individual walls).

The decisive influence is the quality of stitching the

images and maintaining the correct image geometry

throughout the entire installation.

1.2 The Aim of the Article

The main aim of this paper is to present the stitching

subsystem in the SEMI-CAVE laboratory. The

geometrical integration of the images is one of the

most important task in preparation of the VR

installation environment. The proposed and tested

tools in SEMI-CAVE allow for correcting geometry

of the displayed images regardless of the projector

settings, always in the same, easy way.

2 THE STITCHING PROBLEM IN

CAVE INSTALATION

The most advanced VR installation called CAVE

(Cave Automated Virtual Environment) was

introduced in 1991 (Cruz-Neira et al., 1992). Using

this idea, several different solutions (CAVE2, wall

of monitors) were created later (Kim et al., 2013).

There are also many publications on the technical

aspects of CAVE solutions. The review works

deserve special attention (Zhou et al., 2009, Kim et

al., 2013, Muhanna, 2015).

The problem of stitching images in CAVE

installations involves two independent issues; both

are essential for our SEMI-CAVE laboratory:

• display stitching, and thus stitching to correct

the properties of display devices. Aspects such

as changes and inaccuracies in projectors

position, changes and differences in

displaying information are taken into account;

• panorama stitching, thus stitching the images

prepared for display in the CAVE installation.

In our laboratory also, the previously prepared

fragments must be combined into a single

unit, which enables proper display in the

entire SEMI-CAVE installation (on all walls).

2.1 Display Stitching

In an ideal (theoretical) situation, the projector

should be set so that the image it generates is

perfectly rectangular (undistorted). At the same

time, the image generated by this projector is

adjacent to the second image in such a way that

together they form a coherent image with an

unnoticeable boundary (connection). Of course, this

situation should occur for each pair of neighboring

images and the projectors that generate them. In

practice, it is not possible to achieve such an ideal

situation. Additionally, all parameters of device

(including optical) change (degrade) over time. The

only way to solve this problem is to use software

that corrects the image geometry. The software

should meet the following requirements:

• the possibility of geometry correction on the

principle of converting a quadrilateral into a

quadrilateral with the determination of

appropriate colors inside the resultant

quadrilateral by interpolation;

• software support implemented by means of a

simple, intuitive interface enabling easy shape

correction;

• the ability to visually check the correctness of

the proposed geometry correction by using (or

comparing with) a well-recognized pattern;

• two software operating modes: standard mode

(when displaying images) and editing mode,

during which geometry and color can be

corrected. It can be assumed that the editing

mode (correction) will be used relatively

rarely (once a month or less frequently);

• the correction mode of the software should,

above all, meet one basic condition. It must

work all the time while displaying each image

in the SEMI-CAVE installation. The

implementation of this task should be done in

the most effective way, using the computer

resources as little as possible.

2.2 Panorama Stitching

Currently, several algorithms are used to combine

images. The most popular methods based on feature

extraction are the SIFT and SURF algorithms. SIFT

(Scale Invariant Feature Transform) was proposed

by David Lowe in 1999 (Lowe, 2004). Initially, it

only included the problem of detecting the object,

that was sought in the photo. It was quickly

extended to stitch fragments (Evans, 2009) and to

the creation of panoramas (Hess, 2010). The SURF

(Speeded Up Robust Features) algorithm was

developed by Herbert Bay in 2006 (Bay et al.,

2008). It is used to detect and describe images based

on characteristic points (Evans, 2009, Hess, 2010).

The SURF algorithm is partially based on SIFT, but

is estimated to be several times faster in its standard

form than the SIFT. (Schweiger et al., 2009).

Geometrical Picture Integration in SEMI-CAVE Virtual Reality

101

2.3 Quadrilateral into Quadrilateral

Transformation

Let points T

define quadrilateral. We are

looking for a transformation

, which allows for

converting quadrilateral T

into quadrilateral

assuming the appropriateness of vertices.

Vertex T

is converted to vertex P

(Figure 1).

Conversion of a quadrilateral into a quadrilateral

is a geometric problem occurring in computer

graphics (Heckbert, 1989), image processing

(Bahram, 2002) and machine vision (Davies, 2005).

Figure 1: Transformation of the quadrilateral T

into the quadrilateral P

From a formal point of view, the transformation

of a quadrilateral into a quadrilateral is described by

homographic functions. This issue we can find in

many books related to image processing. The

simplest solution to this problem is to propose an

algorithm that uses a bilinear transformation.

Comparative analysis of various solutions of this

problem (Augustynowicz and Sawicki, 2016) shows

that it is difficult to indicate one universal algorithm

that would always carry out the task in the most

effective way. In specific conditions of a particular

application, it is worth considering the choice of

method. Nevertheless, in contemporary textbooks

(Hartley and Zisserman, 2004), the authors

recommend the DLT (Direct Linear Transformation)

algorithm (Abdel-Aziz and Karara, 1971) as the

best, practically universal solution. At the same

time, the DLT method is often cited in the literature

as the basic method for camera calibration in the

implementation of projection (Bardsley and Li,

2007, Dubrofsky, 2009).

3 SEMI-CAVE LABORATORY

Our installation (SEMI-CAVE) was dedicated to

study the impact of visual environment of the

workplace on human psychophysiology. The VR

installation and the virtual environment created in

this way should allow different working tasks to be

performed in a proper – specific environment. This

way the most important argument for choosing the

type of VR installation was the need for relatively

large room dimensions (VR space). We have

assumed that our virtual reality will be realized in a

room of dimensions: 8.6m x 4.3m with internal

projection. The minimum height of the image on the

wall is 2.8m and there are no images on the floor

and the ceiling. Such assumptions provide a

practical compromise between the simulations of the

working environment and the immersion benefits of

the virtual environment. Details of SEMI-CAVE

technical aspects were presented in (Sawicki et al.,

2017).

Figure 2: Arrangement of projectors that create six images

on the four walls.

We used six projectors for displaying images

(Figure 2). The main parameters are: brightness at

the level of 4000 lm ANSI, WUXGA resolution

(1920x1200), LCOS matrix, short throw optics with

Lens Shift and Keystone Correction in two

directions. These parameters make it possible to

obtain the expected shadow-free work area. The

projector has a built-in edge blending mechanism

which allows for basic stitching of the images. This

mechanism was used in the initial stage of the

installation. Initial, precise settings of projectors and

their hardware calibration ensured the correct

display and stitch of images. However, growing

mismatches have been observed over time. They

mainly result from vibrations and aging of the

supporting structure on which the projectors are

mounted. The problem turned out to be so important

that a few months after installation, there are

significant deviations between the images displayed

by individual projectors. This has an important

impact on the perception of images, and thus on

immersing into VR. Using the installation for a year

has shown that from time to time a correction of the

image stitching is required.

The standard operating scheme in our laboratory,

as in CAVE installations, allows for separating the

work of visualization algorithms into stages. On the

CHIRA 2018 - 2nd International Conference on Computer-Human Interaction Research and Applications

102

other hand, stitching the panorama in the SEMI-

CAVE installation is a rather rare task, although it is

necessary to combine real images with VR. It is

advisable to use known and available software

packages that allow for professional combination of

panoramas. A well-known analysis of the available

software (Comparison, 2018) has been published

and shows that Hugin program is currently one of

the most effective programs using feature extraction

methods (Hugin, 2018). This program uses the

PanoTools library (PanoTools, 2013) and is free

software distributed under the GNU GPL. An

additional advantage is that it is a software that

allows you to use a very wide set of different

projections – in particular: rectilinear, cylindrical,

spherical, and many others such as Mercator and

sinusoidal projections. This advantage was decisive

when choosing a solution – the proper projection in

CAVE installations has a decisive impact on the

immersion in the virtual world.

The camera calibration is compatible with the

calibration of projectors in the SEMI-CAVE

installation. Analyzing these known solutions, we

assumed that the DLT method is practically the best

solution to the problem of quadrilateral to

quadrilateral conversion for the SEMI-CAVE

installations. On the other hand, in our software the

algorithm of transformation will be used in two

situations: as a standard driver at the shader level

and as one of many applications for preparing

images of real objects to be used in SEMI-CAVE.

4 PROPOSED METHOD OF

CORRECTION FOR DISPLAY

STITCHING

In a small room of a typical CAVE installation (e.g.

2m x 2m x 2m), the VR space in relation to the real

space can be set practically arbitrarily. Even slight

deviations from the vertical should not be

noticeable. It is enough to match the quadrilateral

images between each other to stitch the images. In

SEMI-CAVE we deal with relatively large real

space and stitching operation is not so simple. The

basic problem is the need to define the reference

level of the VR space and match it to the selected

reference level of the real space. Theoretically, this

is the adjustment of the horizon, but in practice

"horizon" may mean a certain pre-arranged reference

level relevant (and important) to the given content of

the displayed image.

We assumed that the horizon line can be

independently defined for each image. This means

that it can be placed in any image height defined

independently (Figure 3). This approach gives the

possibility to define a common horizon line for all

six displayed areas in a convenient way. The horizon

understood in this way becomes the reference line

for the displayed information in the entire SEMI-

CAVE installation. It is worth emphasizing that in

such a situation it is possible to determine the

horizon line in the displayed areas, and then

compare this line (and its possible correction) with

the line pattern obtained from the laser level set in

the SEMI-CAVE laboratory. This allows eliminating

cases where the images are properly stitched

together, but the entire set of images is distorted. It

should be remembered that in a large spaces, VR

and real, it is very difficult to control distortion of

global geometry when the user corrects local

stitching. The horizon line as a reference level in the

whole space (laboratory) makes this correction task

much easier.

Figure 3: The position of the horizon line (red) arbitrary

defined at the bottom of images.

At the software level each of the six displayed

images functions independently and is displayed

independently. The configuration of each display is

also implemented independently. This approach to

display gives the possibility of individual geometry

settings, and thus gives the opportunity to correct

individual geometry for each of the projectors.

In the management of the display at the graphic

card level, we have adopted a normalized area

defining the geometry of the displayed image. It is

defined by the square {(-1,-1), (1,-1), (1,1), (-1,1)}.

After the first selection of the position of the horizon

line (y_hor selection), this area will be split into two

rectangles:

upper {(-1,y_hor), (1,y_hor), (1,1), (-1,1)}

lower {(-1,-1), (1,-1), (1,y_hor), (-1,y_hor)}.

Geometrical Picture Integration in SEMI-CAVE Virtual Reality

103

This allows for independent correction of both

rectangles. In this case, the operator can change the

position of six points. However, for the four vertices

of the normalized square it can change both x and y

coordinates, while for the two vertices associated

with the horizon line, only x coordinates (y

coordinates for this line were set at the horizon

definition level).

Figure 4: The GUI control panel of the software for

stitching display in editing mode. The step of changing

horizontal line position is selected (horizon mode). There

is a possibility to change position of the horizontal line

with the mouse or by entering a number that is the

proportion of the position relative to the height.

The software for stitching the display in the

editing mode gives the possibility to modify the

position of the respective elements in several steps.

In the first step, the operator selects the position of

the horizon using the GUI (Figure 4). Operator has

two possibilities of changing the position: by the

value of proportion (y position of the horizon line in

relation to the high of whole screen) or by the

position movement (by mouse). In the next step

there is possibility to align the VR horizon to real

horizon. It can be done by moving the whole image

up or down. In this step laser level is required as a

special additional equipment. In the third step

(vertices mode), the operator can intuitively

reposition the selected vertex using mouse

movements. (Figure 5). This approach gives very

wide possibilities to change the shape of the area to

ensure the adaptation to practically any conditions of

physical display by projectors. And it is

implemented in a simple and intuitive way. On the

other hand, the horizon line provides a reference

level that is not ensured by changing only the

position of vertices.

Figure 5: The GUI control panel of the software for

stitching display in editing mode. The step of changing

vertices position is selected (vertices mode). Position of

each can be changed independently with the mouse.

In addition, in the last step (clipping mode) the

operator can define the position of clipping lines in

order to clip the image to the standardized area. In

this mode only the position of the main vertices

(without horizon vertices) is taken into account

(Figure 6). Using this operation, the edges of

neighboring images can be independently aligned

(on a common wall or in the corners of the room).

The full algorithm for geometry correction in

SEMI-CAVE is as follows:

1. define the horizon level for the entire VR

space;

2. for each image: define the appropriate horizon

line (according to VR horizon level);

3. display the level of the (real) horizon by using

the laser level in the position closest to the

displayed horizon lines from the VR space;

4. for each image: adjust the image position to

match the horizon of the VR space to the

horizon of the real space;

5. for each image: adjust the position of the

vertices, according to stitch images in pairs

(pairs that are adjacent);

6. for each image: define clipping line for the

image, according to pairs of images (pairs that

are adjacent).

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The image stitching subsystem has been

implemented at the shader level for the graphics card

processor. The software has been prepared in the

Visual Studio environment. For operating graphics

in the working mode, the Vulkan environment was

used (Sellers and Kessenich, 2016, Overvoorde,

2017). This is the most modern and probably the

most interesting technology currently used to

program advanced graphics. In the edit mode,

OpenGL environment was used. All implemented

operations within the appropriate shader have

hardware representations in the graphics card

processor. On the other hand, the division into

appropriate procedures in OpenGl and Vulkan was

designed to achieve the maximum performance of a

given processor. Moreover, since Vulkan is a

continuation of OpenGL and both libraries were

procedures in them can easily be used

interchangeably. This has been effectively applied in

the SEMI-CAVE software.

Figure 6: The GUI control panel of the software for

stitching display in editing mode. The clipping mode is

selected. Position of four vertices can be change

independently with the mouse.

5 VERIFICATION OF THE

SOLUTION

As part of the initial software tests, the correctness

of the implementation of individual operations was

checked and the work of algorithms for different

ranges of geometric correction was analyzed. Next,

we carried out the geometry correction in real

conditions in the SEMI-CAVE laboratory.

Verification of the proposed solution should be

related to the evaluation of the stitching correctness

and appropriate usability tests. However, in our

conditions it is very difficult. The images are either

properly stitched or not – it is difficult to analyze

intermediate states. Therefore, we have proposed a

simple metric that gives the answer whether the

correction is done well. The control images (grid

pattern) are designed in such a way that the

positioning of the corresponding control points can

be determined with accuracy to a single pixel. On

the one hand, such accuracy is sufficient to assess

the correctness of stitched images; on the other hand,

practically no better resolution is possible.

The first step in testing the developed software

for geometric correction was to stitch different

component images, including combining images in

the area of display on one (common) wall with two

projectors and in the corners of the room where the

adjacent images were displayed on adjacent walls.

We have developed control images using the black

and white grid of squares displayed in the positive or

negative version. They were chosen for the testing

and correcting the images geometry. The control

images facilitated the work greatly.

Figure 7: Area where two component images from

different projectors are displayed. a) The white rectangles

are displayed. b) The grid squares are displayed as control

images. Visible shift of images.

The final tests were done in SEMI-CAVE, in the

real arrangement of projectors, the positions of

which had not been adjusted. The aim of these tests

was to adjust and correct the real geometry. These

tests were carried out after about a year after the

Geometrical Picture Integration in SEMI-CAVE Virtual Reality

105

projectors’ hardware was set up (calibrated) of. Such

a long working time caused that the influence of

vibrations and aging of the mechanical elements of

the construction impacted the changes in the position

of projectors. Figure 7 shows a picture of an

example area in which two images from neighboring

projectors are displayed per wall. Visible, clear

shifting of the images reaches a size of

approximately 2 cm.

The consequences of decalibrating the position

of projectors are visible on the example images of

the Warsaw Saski Garden displayed in SEMI-

CAVE. Figure 8 shows a fragment with a clearly

visible divergence of component images. Figure 9

shows an enlarged fragment of images of the

Warsaw Saski Garden with clearly visible improved

display geometry. This is a fragment of the area

shown in Figure 8.

Figure 8: Area where two component images from

different projectors are displayed. The consequence of

shift of images presented in Figure 7.

Figure 9: An enlarged part from area shown in Figure 7

after correction. We can see the correct (uniform) border

between the lawn and the path.

It is worth noting that the possibility of

displaying images in the SEMI-CAVE installation is

possible only after closing the editing mode of the

stitching subsystem. This means that the correction

software sets the correction rules in the editing

mode, and the rules are apply at any time during the

software operation (in the display mode) and are

valid until the next change in the editing mode. Thus

the view, the fragment of which is shown in

Figure 9, can be displayed after the correction in

stitching mode and then after closing this mode.

Similar examples of corrections have been made

many times in the SEMI-CAVE installation for

different display areas. All experiments were

successful – just like the views presented in the

article. The correctness of the conducted tests

confirms the correctness of the introduced solution

concept, as well as the correctness of the software

implementation.

6 SUMMARY

In the article, we described the problems of stitching

images in a complex CAVE installation. We have

proposed the method to solve the problem and

developed the proper stitching subsystem. The

subsystem allows for combining individual images

to ensure the correct geometry in the displayed

space. In addition, our stitching subsystem gives full

control over the image creation process, which is an

important advantage of our own solution.

The relative large size of the real space in SEMI-

CAVE required a different, more advanced stitching

approach than used in typical CAVE applications. A

good solution facilitating the work was the horizon

line with the possibility of arbitrarily setting its

level. The experience and methods of stitching

images in the panorama were also very helpful.

The image stitching subsystem has been

implemented at the shader level and it is directly

executed by the graphics card processor. This

guarantees low CPU load of the main computer by

the whole task of geometric correction. The software

has been prepared using Vulkan – the best

contemporary technology for advanced graphics

programming.

We have conducted a series of tests in the real

conditions of the SEMI-CAVE laboratory. The tests

confirmed the correctness of the proposed solutions.

The interface for setting correction parameters in the

form of appropriately prepared GUI proved to be

very convenient in use. The best confirmation of the

stitching subsystem operation is the good impression

of immersion into VR after the geometry correction.

CHIRA 2018 - 2nd International Conference on Computer-Human Interaction Research and Applications

106

ACKNOWLEDGEMENTS

This paper has been based on the results of a

research task carried out within the scope of the

fourth stage of the National Programme

"Improvement of safety and working conditions"

partly supported in 2017–2019 within the scope of

research and development --- by the Ministry of

Science and Higher Education / National Centre for

Research and Development. The Central Institute for

Labour Protection -- National Research Institute is

the Programme's main coordinator.

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