Relief shape inheritance and graphical editor for the landscape design

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Relief shape inheritance and graphical editor for the landscape design Egor A. Yusov Vadi E. Turlapov Nizhny Novgorod State University after N. I. Lobachevsky Nizhny Novgorod Russia yusov_egor@ail.

1 Relief shape inheritance and graphical editor for the landscape design Egor A. Yusov Vadi E. Turlapov Nizhny Novgorod State University after N. I. Lobachevsky Nizhny Novgorod Russia Abstract In the context of this work a nuber of rules for landscape design editor developent are proposed. These rules are aied at the support of the reciprocal influence of the relief and obects located on its surface. An experiental graphical editor of dynaic 3D scenes has been created on the basis of relief shape inheritance principle (inheritance of z coordinate of any obect). Various inheritance rules (including obect binding to the specific point continuous and discrete obect dependence on the relief) as well as efficient landscape odification ethods are ipleented in the editor. The progra also realizes texture apping obects iport fro 3D Studio MAX obects oveent along the defined traectories water surface odeling. A landscape reconstruction algorith according to the coloration of geographical ap has been developed. A new iage filtration algorith is described. Keywords: landscape design 3D-graphics graphical editor relief inheritance landscape reconstruction 1. INTRODUCTION Modeling of terrain with obects located on its surface is one of iportant probles of coputer graphics. Quite often this odeling ust result in creation of panoraic fields of view which can be used in landscape and architectural design or in video siulators and coputer gaes. High-quality odeling of such dynaic scenes requires realization of two conflicting deands [1]. On the one hand virtual odel ust be enough detailed. On the other hand it ust work in real-tie i.e. it ust support a high speed of visualization (not less then 5 fraes per second) during flying around scene. There are any probles in this field of coputer graphics. The ost significant are: landscape reconstruction and its texturing using different data sources; scenery reconstruction according to aps and other sources; relief shape inheritance; siplification of terrain geoetric odel; active environent odeling based on the landscape and scenery; There are a lot of works devoted to the terrain odel siplification. ut the proble of interconnection between landscape and obects is not considered. For exaple in [5] siulating of autonoous vehicles on planet-sized terrain is described but stationary obects like buildings roads etc. are not taken into account by the authors. This paper is ainly concerned with the proble of relief shape inheritance landscape reconstruction and active environent odeling.. PROLEM OF RELIEF SHAPE INHERITANCE In order to solve landscape developent task it is necessary to design 3D editor which allows the user not only to restore 3D scene of a real area by the flat ap with inial expenses but also to easily continue scene odeling (landscape odification obects locating etc.). Nowadays the proble of landscape reconstruction according to topographical plan is solved by any geoinforation systes but 3D odeling of situation is usually absent. 3D Studio MAX [] is the syste which provides the user with capabilities which are the ost close to the deands of applied task. It includes Terrain odule which can restore 3D landscape by the aggregate of isolines closed contours. After landscape has been reconstructed the user can proceed with farther odeling of the situation. However the user has to solve by hand all tasks concerning congruence between landscape and obects which are placed on its surface. If user decides to change relief then he or she will have to anually edit all obects situated on it. If any obects have been already positioned on the landscape surface it would be very inconveniently to update all their locations and fors. This proble becoes ore difficult if obects are coplex and ulti-layer in respect to geoetry and texture or they are built by the eans of artificial intelligence [3] [4]. Figure 1: Relief reconstruction by the facilities of Terrain odule. Thus if you work in 3D studio you should firstly copletely design your landscape and only then start locating obects on it. Otherwise you can be confronted with great difficulties if need to odify relief arises. Scene texturing in 3D Studio alost copletely excludes flying around the scene in real tie.

3. MAIN THESES In order to create facilities allowing easily landscape reconstruction according to a flat plan (ap) it is proposed to introduce into the geoinforation systes and 3D editors relations

The inheritance rules ust confor to the real obect relations including the following: 1) obect binding to the specific point of the landscape surface or another obect with inheritance of its position

2 3. MAIN THESES In order to create facilities allowing easily landscape reconstruction according to a flat plan (ap) it is proposed to introduce into the geoinforation systes and 3D editors relations of relief shape inheritance by the obects. The inheritance rules ust confor to the real obect relations including the following: 1) obect binding to the specific point of the landscape surface or another obect with inheritance of its position by z coordinate; ) reciprocal influence of the landscape and obects located on it (for exaple landscape leveling by the obect s botto side or obect s botto side correction by the relief surface); 3) continuous or discrete obect dependence on the shape of relief on which it is situated (continuous discrete continuous with alignent by direction etc.). 3.1 Types of dependence As it has been said earlier one of the fundaental ethods of landscape and obects interconnection is specifying for obect one of three possible types of dependence. Now we describe these types ore detail Continuous dependence In the process of landscape design a situation when soe obect (for exaple pipe of heating syste wall road and so on) should copletely repeat the shape of relief on which it is located can occur. The characteristic feature of these obects is that their for is directly defined by the terrain surface under the. If landscape under the obect with this type of confority is odified then every obect s discrete part ust autoatically ove in order to correspond to the new terrain state. Figure 3: Krelin wall discretely following the slope on which it is built Continuous dependence with generatrix horizontality retention One of the ost widespread city obects are roads. They should follow the terrain surface on which they are built ust as obects with uninterrupted dependence. ut there is one essential difference: every transverse cut of road top side should always be horizontally. Iportant factor which has an ipact on the obect shape in this case is its centre line or generatrix. It is centre line that allows correct deterining transverse cut of the side. 3D editor ust support this type of dependence. Figure : Krelin wall continuously following the slope on which it is built If relief under the obect with continuous dependence is odified then this obect ust autoatically change its shape so that it confors to the new landscape state. In contrast to systes like 3D Studio MAX the user should not be required to perfor any additional actions to achieve this confority Discrete dependence Along with the continuous dependence when obect flow over the terrain on which it is placed another typical situations can be et. In these situations an obect ust be divided into soe parts according to soe rules and each part ust watch landscape height under it irrespective of the other parts. For exaple a wall built on the slope can be divided into sections and go down like a big stairs (Figure 3). Figure 4: The road for which a continuous dependence with alignent by obect direction is specified 3. Aniation High-grade design of real scenes can not be achieved without obects aniation odeling. During landscape designing obects otion is closely related with landscape shape along which it is perfored. 3D editor ust support various types of oveent of real obects (cars airplanes helicopters etc.): oving along terrain surface flying over the landscape with repetition of its contour or flying on constant height etc. Obects traectories ust be autoatically updated every tie when landscape changes. And it is also the graphical editor s responsibility.

3 4. TERRAIN RECONSTRUCTION ACCORDING TO THE GEOGRAPHICAL MAP There are any ways to obtain terrain shape description. If landscape design is being carried out for a real territory the source inforation for it can be obtained fro a topographic plan which contains the iage of situation and scenery. Flat plan describes landscape surface by eans of isolines and elevations Geoinforation systes usually use flat topographical plans as base source for the reconstruction. However flat plans are not used to describe large regions. Geographical aps are usually utilized for this purpose. Geographical ap keeps inforation about landscape shape in the coloration of the ap. Each ap has their own height scale which sets up a correspondence between colors presented in the ap and real heights of the region. A special algorith which allows restoring landscape by the iage of the original geographical ap has been developed. This algorith has three stages: (1) population of the color levels table which sets up correspondence between colors and heights of the area; () iage filtration and (3) reconstruction itself. 4.1 Iage filtration Purpose Geographical aps usually contain uch subsidiary inforation such as various naes parallels eridians etc. Since algorith being proposed perfors terrain reconstruction based on the coloration of the ap the colors of this subsidiary inforation can not be used to calculate height of appropriate point of the region. Thus it should be reoved fro the ap. This is what the filtration is aied at. Two algoriths have been ipleented: edian filtration and filtration by ean square deviation Description of filtration by ean square deviation algorith For each pixel of the iage the following actions are perfored: 1. An average color in the square area in the centre of which a current pixel is located is calculated. Algorith has paraeter a which defines the size of this area (fig. 5). Figure 5: A square area of the iage in which an average color is calculated The following forulas are used to calculate red green and blue coponents of the average color: R = R R G = G = Where G and are red green and blue constituents of i * a i * i * + a (i pixel. D = i : iin i i averaging area; iin i in following expressions: - is an in } can be obtained using {( * a * * +a i in in = ( i* a) i = in( W i * + a) = ( * a) = in( H * + a) Here W and H are iage width and height correspondingly. = D = ( i i + 1)( 1) is a power of set D. in in +. On the second step a dispersion of colors in the averaging area is calculated by the following forula: ρ = ( R R) + ( G G) + ( ) ) And square deviation of central pixel fro average color is calculated: ρ * = ( Ri* R) + ( G * i* G) + ( * i* ) * 3. If after that the following inequation ρ > * λ ρ is true the color of central pixel is iproved with corrected average color. In the last expression λ 1 is a reection coefficient. It is a second paraeter of the algorith. 4. If centre pixel has to be updated the corrected average color is coputed. Its coponents can be obtained by the following forulas: R Ri = ~ ~ G Gi = ~ ~ ~ = ~ where D = { D : ρi λ ρ } is corrected averaging ~ area; ~ = D - is a nuber of pixels in the set D ~. ~ is always grater than because of the following reasons: ρ * > λ ρ λ 1 included into the set D and ~ consequently ρ * > ρ. Central pixel is ρ * > ρ hence there ust be at least one pixel in the D which has a lesser deviation fro average color than average deviation. Since ~ corrected average color will always be accurately coputed. Excluding pixels which have greater deviation fro the average color than λ ρ allows reducing their influence on the iproved color. Filtration algorith has two versions: continuous and discrete. In the first case filtration is perfored as it has been described above. Discrete filtration takes into account the fact that only soe nuber of predefined colors are allowed for the ap. These colors populate color level table. In case of discrete filtration before soe pixel will be iproved a search in the color levels table of the ost siilar to the corrected average color is prefored. And central pixel is set to this obtained color Median filtration algorith description A second filtration algorith ipleented in the editor is edian filtration. The algorith does the following:

1. For each pixel of the iage a saple of its surroundings of size 3x3 5x5 or 7x7 is perfored ust like for filtration by ean square deviation.

Color of the central pixel is iproved with the color corresponding to the iddle value of intensity in the sorted list. Algorith also has two odifications: continuous and discrete.

4 Algoriths coparison Figure 6 shows initial iage of the ap figure 7 shows results of filtration by ean square deviation algorith and figure 8 shows results of edian filtration.

In this stage the filtered iage is uniforly stretched on the terrain frae and for each node a height is calculated.

A height of each color in this area is calculated and average height is assigned to the node. Diensions of this area depend on the ratio of ap iage and terrain frae sizes.

p i Map iage q W H Figure 7: Continuous (on the left) and discrete (on the right) ean square filtration results Figure 1: A landscape reconstructed by the geographical ap of Africa 5.

4 1. For each pixel of the iage a saple of its surroundings of size 3x3 5x5 or 7x7 is perfored ust like for filtration by ean square deviation.. Pixels of the saple are arranged by its intensities which can be calculated using the following expression: I=.3R+.59G Color of the central pixel is iproved with the color corresponding to the iddle value of intensity in the sorted list. Algorith also has two odifications: continuous and discrete. In the second case color of central pixel is iproved with the color for the table which is the ost siilar to the edian color Algoriths coparison Figure 6 shows initial iage of the ap figure 7 shows results of filtration by ean square deviation algorith and figure 8 shows results of edian filtration. Figure 6: Initial iage of the ap 4. Terrain reconstruction After geographical ap iage has been cleared fro the additional inforation a terrain reconstruction itself can be carried out. In this stage the filtered iage is uniforly stretched on the terrain frae and for each node a height is calculated. In order to ake terrain ore sooth nodes heights are coputed based on the square iage area in the centre of which a pixel corresponding to the node is situated (fig. 9). A height of each color in this area is calculated and average height is assigned to the node. Diensions of this area depend on the ratio of ap iage and terrain frae sizes. Terrain frae y x H lnd W lnd Figure 9: Frae node and corresponding sooth area of the iage Figure 1 shows snapshot of Africa terrain reconstructed by the original geographical ap. p i Map iage q W H Figure 7: Continuous (on the left) and discrete (on the right) ean square filtration results Figure 1: A landscape reconstructed by the geographical ap of Africa 5. DESCRIPTION OF THE DEVELOPED EDITOR Figure 8: Continuous (on the left) and discrete (on the right) edian filtration results Figures reveal that the best result is obtained when discrete filtration by ean square deviation algorith is used. In order to investigate effectiveness of suggested inheritance facilities an experiental version of 3D editor which uses in practice all theses listed above has been developed. Experiental editor realizes different inheritance rules (for instance obect binding to the specific point all kinds of dependence). A nuber of special relief editing ethods (which include different types of surface deforation interpolation shifting etc.) are also granted by the progra.

5.1 Rando landscape generation The editor defines landscape as a height atrix. One possible way to obtain this atrix and to siulate unknown area is to generate it using rando nuber generator.

Figure 1: Using of odels iported fro 3D Studio MAX during scene design 6.

5 5.1 Rando landscape generation The editor defines landscape as a height atrix. One possible way to obtain this atrix and to siulate unknown area is to generate it using rando nuber generator. A special land producing algorith based on the Peril s noises has been developed. Selecting different values of generation paraeters allows producing various landscapes. Figure 1: Using of odels iported fro 3D Studio MAX during scene design 6. CONCLUSION Figure 11: The landscape obtained using rando nuber generator A good ethod of iproving landscape quality which used in the progra is to color it depending on the height. This eans that low regions of surface have blue color (they iitate water); green (color of grass) is assigned to the higher regions; it is followed by the brown (ountains) and the highest regions have white color (they odeling snow on the tops of ountains). 5. Additional capabilities The following features have been also ipleented: texture apping on the landscape and obects; fogging; odeling of different types of scene illuination and characteristics of landscape surface; obect iporting fro 3D Studio MAX; water surface odeling; a library of standard obects. Solutions which are assued as a basis of the editor allow the user to fly around textured scene being designed in real tie even on a coputer without 3D accelerator. A high speed of aniation is achieved on the coputer with 3D accelerator. Direct 3D is used as base graphical progra software. As a whole experiental version of the graphical landscape editor confirs efficiency of obects location inheritance by z coordinate facilities. Inheritance instruent and eans of landscape reconstruction according to the flat geographical ap can be easily introduced into the instruental geoinforation systes with obect data structure. 7. REFERENCES [1] Mikhailuk M.V. Coputer graphics for video siulator // Proc. of the Conf. of Coputer Graph. and Visual. - GraphiCon' N. Novgorod 16-1 sep.. [] Murdock K.L.. 3ds 5. ible. Wiley Publishing Inc p. [3] Diitri Pleenos D. Miaoulis G. Vassilas N. Machine Learning for a General Purpose Declarative Scene Modeller // Proc. of The Conf. of Coputer Graph. and Visual. - GraphiCon' 16-1 sep. p.3-3 [4] Sosnov A. Huot S. Mace P. Hegron G. Rapid Increental Architectural Modeling fro Iprecise Perspective Sketches and Geoetric Constraints // Proc. of the Conf. of Coputer Graph. and Visual. - GraphiCon' N. Novgorod 16-1 sep. p.4-49 [5] Selcuk Suengen Seli alcisoy Real-tie siulating of Autonoous Vehicles on Planet-Sized Continuous LOD Terrains // Conference Proceedings ISN WSCG 5 January 31 February 4 5 Plzen Czech Republic. About the author Yusov Egor - student of Nizhny Novgorod State University after N.I. Lobachevsky Departent of Coputational Matheatics and Cybernetics. E-ail: yusov_egor@ail.ru Turlapov Vadi - professor of Nizhny Novgorod State University after N.I. Lobachevsky Departent of Coputational Matheatics and Cybernetics. E-ail: turve@pent.sci-nnov.ru

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