Aishah Abdul Razak Faculty of Information Technology, Multimedia University,63100 Cyberjaya, Selangor, Malaysia

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1 Comparison of High Dynamic Range Images (HDRI) rendering technique with normal rendering for integrating 3D architectural model into 2D local environment Aishah Abdul Razak Faculty of Information Technology, Multimedia University,63100 Cyberjaya, Selangor, Malaysia Mohd Izani Zainal Abidin Faculty of Creative Multimedia,Multimedia University Cyberjaya, Selangor, Malaysia Dr. Ahmad Rafi Eshaq Faculty of Creative Multimedia,Multimedia University Cyberjaya, Selangor, Malaysia ABSTRACT This paper presents our attempt to explore and utilize High Dynamic Range Images (HDRI) as a method to generate photorealistic renderings, particularly in local 3D architectural visualizations. First we present an overview of HDRI, the definition, application and advantage. For the purpose of experiment, a database of HDR images have been collected and generated. This consists of indoor and outdoor images, and these images have been converted to HDRI using special software known as HDRIshop. An experiment has been carried out to compare the results of HDRI rendering and normal (traditional) rendering in terms of quality, rendering time and memory usage. Based on the results, it has shown that HDRI rendering has major advantage over normal rendering such as it produce more realistic rendering with less rendering time and memory usage. Finally the authors conclude the rendering quality and the effectiveness of the methods discussed and suggests some recommendation to further explore and expose the method in the field of architectural visualizations. Key Words: HDRI, rendering, architectural model, visualizations 1. Introduction Rendering architectural objects (elements/buildings) using photorealistic rendering approach is a very complex process. With the advancement of the computer technology and its speed, high expectation has been given to the photorealism, details and believability. With today s rendering technology, viewers are expecting more realistic rendering approach can be achieved for final presentation.in 3D computer graphics today, we have seen many rendering approaches were invented. These rendering approaches have been used in many popular applications such as architecture, games and entertainment. Commercial rendering software has been invented by several 3D graphics developers in this field. This ranges from global illumination (GI), final gather (FG), radiosity and etcetera. Some 3D artists used to stick to one rendering software and others used to combine several methods. Combination technique allows more opportunities and more realistic output can be produced. In the case of architectural visualization, two rendering approaches namely pre-rendered

2 and real-time simulation which is commonly known as 3D simulation can be used. In this paper we focus on generating HDRI inputs by using local series of environment photos. All of the images are rendered using 3D Studio Max 6 through its native rendering method. The beauty of Mental ray rendering outputs is unquestionable. Since HDRI is one of the popular methods to render 3D objects realistically, thus the use of HDRI is expected to improve the quality of the rendered output.....ss 2. Motivation This project was motivated and inspired by the use of advanced rendering technology for photorealistic rendering. Instead of using commercial HDRI library from the market today, the researchers find own initiative to capture and create HDRI library from local scene, in this case the scenes are shot from Taman Mini Malaysia, Malacca.. The reason of choosing local environment is because it has a strong context with the local culture and local architectural elements. This HDRI library will be used for rendering 3D objects and integrating them into real background. With the introduction of HDRI technique more accurate result can be obtained when combining 3D objects into real image. This allows a seamless integration can be made and the final output is more realistic and believable, in some cases viewers cannot even notice the 3D objects. As explained by Renner [1]" There is no other way to capture reality more precisely than with the method of HDRI ". Motivated by this scenario, the researchers would like to explore and experiment this technique for local architectural scene.our main objective is to integrate 3D objects into local architectural environment and compare the quality of rendering based on using normal rendering technique and HDRI technique. The comparison will be based on several key elements. The final output should be seamlessly integrated and rendered. Photorealism is the main goal for this experiment. Choosing this method is based on suggestion by Szécsi et al [2], "When virtual objects are illuminated by a realistic sky model [3, 4, 5, 6] or when these objects should be placed in real scenes, the illumination coming from the sky or from a real environment is usually represented by an environment map defined by a high dynamic range image [7, 8].." 3. Intorduction to HDRI Dynamic range is best described as the ratio between dark and bright regions as what is present in the real world. This can be done by taking a series of images with different exposure settings. When these images are combined into one single image, it is also known as radiance map. Radiance map plays an important role when comes to the combining of 3D objects into live action plate. It is used as a light source to illuminate 3D objects in a realistic compositing. In general what makes HDRI different from LDRI (Low dynamic range image) is because of its information stored in the file itself. LDRI normally referred to the normal bitmap such as JPEG,BMP and TIF. These file types are represented by 8 bits per pixel which its value range is limited between and in RGB mode. This is sufficient for representing an image to be displayed on a computer screen, but does not allow the full range of light intensity which is present in the real world to be represented. High dynamic range image formats allow a much greater range of intensity values by using floating point values. The HDR format stores the amount of light every pixel represents instead of on-screen colours that normal bitmaps do. A pixel in a HDR image is defined by floating point numbers such as or It is then possible to represent images [3] which contain the sort of variation in intensity which is found in the real world, without loss of precision. As the results, using this method, the line between reality and computer generated images will further blurs, even when rendering the most difficult real-world features, including hair, fur and human skin. In order to display such images on current

3 computer screens some form of tone mapping would be used. To use HDRI technique, a file of HDRI from the environment must be captured and created. This can be done in two ways; expensive and economical way. Expensive method relies on a well equipped camera system with fish eye lens and economical method can be carried out by using a reflective chrome ball. Both have its advantages and disadvantages The use of HDRI In reality, HDRI is used for two purposes namely as: i- It is very straight forward, instead of using normal reflection map, one can use HDRI as a reflection map. Figure 1[9] illustrates the use of HDRI as a reflection map. Using this method, more accurate rendering can be achieved Figure 2 illumination with different HDR images/exposures[9] 2.2 The use of HDRI In general there are four types of output from HDRI environment maps. These types are explained in Table 1 below. Table 1: Four types of output from HDRI environment map No Illustration Description 1 Figure 1 Example of Reflective HDRI [9] 2 Light probe Vertical cross ii. Light source Major application for HDRI is for illumination. HDRI file can be used as a light source and to make it more realistic, it can be rendered through global illumination rendering process. Light source can be done by using HDRI as an environmental map or as a texture map which is mapped onto polygon surface. Figure 2 illustrates the illumination with different HDR images/exposures[9]. Horizontal cross Panorama 2.3 Advantage of HDRI HDRIs are the perfect new technology for two reasons. Firstly, the simplicity inherent in using a single image to light an entire scene allows the creation of more accurate images faster. Not only do HDRIs provide vastly enhanced levels of realism, but also avoid the need to painstakingly set up complex lighting arrangements. Secondly, they allow lighting to be perfectly matched to background images and environments. If this were to be done with an external building shot, the surrounding HDRI

4 would be able to provide not only a convincing approximation to natural daylight conditions, but also include the surrounding environment reflections. All of this along with the environment mapping and reflection possibilities, provides a simple-to-use yet incredibly powerful realism tool [ lightworks- user.com/ hdri.htm]. 3. HDRI database development For the purpose of experiment, we have developed a database of HDRI images. The scenes/ environment is shot at Taman Mini Malaysia consisting of indoor and outdoor scenes taken around am to noon. For each scene, we capture one image using standard lens to be used as the background image and 5 sequences of images with different exposures using fisheye lens to be used for the HDRI file. These photos is then converted into a single file of HDRI and later it is integrated with our 3D model. To generate a HDRI the following steps are involved: 3.1 Scene sekection The scene selection can some times be tricky, such as, scenes which appear nice and clear and full of light might have only a limited illumination effect, when used as a light source later. In general, although a light meter can be handy to measure the available light variation, scene selection is a lot to do with the intuition of the photographer. An expert photographer will now when is the correct time and which is the correct scene to shoot which will produce a good illumination effect on the HDRI image. Four types of scenes have been identified which are shown in the table 2 below: LDRI Shoots Once the scene has been selected, the next step is to shoot the scenes in LDRI format, in our case, we have chosen jpeg file format. For each scene, we capture it 5 times with different exposures. This is done by varying the aperture value between f2.8 to f11. The range of aperture value differs from one scene to another due to the available lighting at the scene at the shooting time. It is very important to ensure that there is no moving object in the captured photos. This can be done by using sturdy tripod and capturing the image sequence with minimum time gap. Sample of sequence images are shown in Table 2. Table 2: Selected scenes for experiment No Category Scenes sequence 1 Indoor1 2 Indoor2 3 Outdoor1 4 Outdoor2 3.3 HDRI Formation HDRI formation is the process of generating one HDR file, containing the properties of the captured LDRI sequence, such as all the bright and the dark regions present in the scene. This can be done via

5 access to HDR shop. To generate a single HDR, we have to load the sequence image, select the camera curve and enter the relative brightness values. images into.now the HDR image has successfully created based on the sequence images. It should be noted that the resulting HDRI file is dependent on the captured source sequences. Thus, it is very important to ensure that the correct scene has been selected from the beginning. 4. The experiment In the experiment, we try to render a 3D model into the selected scenes using normal rendering and HDRI rendering method.3d Studio Max is used as the platform for this experiment. The complete stages involves in this experiment are listed below: 4.2 Modelling a 3D model as the architectural element. 3D models as in figure 6 have been modelled and textured as our architectural element. The models consist of simple geometry like ball, teapot and cylinder. Figure 6 3D model 4.3 Integrating 3D model into actual environment The 3D model developed earlier is now integrated into our selected background images from the database, which is in 2D, by using two rendering methods; HDRI and normal scanline rendering. Figure 7 illustrates this process. In both methods, the major challenge in this task is to provide necessary lightings to get realistic result. During the rendering process, the rendering time and memory usage (virtual and physical) of both methods are recorded for comparison. Figure 7 Integrating 3D model into actual environment 5. Results and discussions The aim of our experiment is to compare the quality of final image achievable using HDRI and normal scanline rendering when we integrate a 3D model into a 2D environment. In general, the process of integrating a 3D model into a 2D environment has to tackle two issues. They are; placement of the object in the scene and re-production of the actual lighting situations. Placement issue might not be a big issue since this can easily be done. However, lighting has always been a major issue in this process. In normal scanline rendering, the lighting is achieved by adding lights into the environment. This is done by trying to match the artificial lighting with the light source available in the background environment. In other word, we approximate the property of the illuminance (the energy received indirectly at the camera). However, the background environment might not be a sufficient lighting source as the illumination spectrum is limited and it doesn t cover the overall environment and its effect. In the case of HDRI rendering, instead of approximating the illuminance, radiance map is used for the lighting. This is collected from the light that is reflected off from the scene and enters the camera,

6 which is known as the illuminance)[ /HDRI/]. Recall that, the HDR image consist of 5 sequences of images with different exposures using fish-eye lens. The use of fish-eye lens allows generation of a very wide angle view of the scene around a point. Once this information is known we only need to know the mapping to relate back to a point in the scene. Coincidentally we will also know an accurate value for the radiance at that point. This allows us to build a virtual set in the computer with light based on the original plate, and coming from the correct direction. This helps us to seamlessly integrate live background and computer generated foreground elements. Figure 8 and 9 illustrate a preliminary result of integrating a 3D teapot model into a 2D background image using normal rendering and HDRI rendering respectively. In both methods, we have added one artificial light for reflection and illumination. Note that in the figures, the front teapot is the integrated 3D model while the backward teapot is originally in the background image. Based on these two figures we can see that the integrated 3D teapot in figure 9 is more realistic compared to the one in figure 8. This is because the way HDR image lights the scene have created a feeling of warmth and a greater degree of realism, especially a ppa r e nt i n t he s ha dowi ng Figure 8 Result of normal rendering Figure 9 Result of HDRI rendering For more detail analysis/ observation, we have rendered all of the integrated selected s c e ne s a nd pr e s e nt i t i n Ta bl e 3. From the figures we can see that HDRI rendering produce shadow which is more realistic and softer compared to normal rendering method. The data from the HDRI image is more accurate since it is using floating point as explained before compared to normal bitmap which relies on RGB (0-255 colours). Table 3: Comparison of final output using normal lighting and HDRI based lighting Normal lighting HDRI based light Indoor 1

7 Indoor 2 Outdoor 1 Outdoor 2 Table 4: Comparison of rendering time and memory usage for normal rendering and HDRI rendering Indoor 1 Indoor 2 Outdoor 1 Outdoor 2 Normal HDRI Normal HDRI Normal HDRI Normal HDRI Rendering time Physical 630 MB 503 MB 627 MB 506 MB 629 MB 507 MB 629 MB 504 MB Memory Virtual Memory 513 MB 465 MB 509 MB 471 MB 513 MB 471 MB 513 MB 465 MB 6 Results and discussions From the result of the experiments, we can see that HDRI method has major advantages over normal rendering method. Overall performance has shown that HDRI method gives more realistic rendering output compares to normal rendering. It is noticeable that the shadow produced by HDRI rendering is softer and realistic compared to normal rendering method. Besides, using normal rendering method, 4 sets of lights are needed to achieve a realistic output, while for HDRI rendering, no additional lights have been added. This is because it totally relies on HDRI environmental map as the light source. Consequently, this reduces the rendering time because additional light would increase rendering time, and thus give

8 another advantage over the normal rendering. Even though the average duration gap is just between 1 to 4 second, however, in the case of animation rendering, this is a major drawback. Additional lights usage has also cause normal rendering to use more memory (virtual and physical) compared to HDRI rendering method. Based on the result, it has shown that HDRI has a very wide potential in the application of architectural visualisation. However the experiments carried out here were based on simple geometry and 3D environment set up and the results may vary based on individual case. Since currently, most of the 3D software support HDRI rendering method, thus this opportunity should be fully utilised. The researchers believe that more exposure should be given to HDRI rendering method because most of the time users tend to relate HDRI rendering method with visual effects and computer graphics movie. Hence the potential of this method for other applications such as architectural visualisation is hidden behind this phenomenon.besides, more tutorial and explanation should be given to HDRI rendering method. It is undeniable that through this research, only minimal amount of the HDRI tutorials are available from the Internet and written document. [4]Henrik Wann Jensen, Michael M. Stark, Simon Premoze,Peter Shirley, Fredo Durand, and Julie Dorsey.A physically-based night sky model. In Computer Graphics Proceedings, Annual Conference Series (SIGGRAPH 2001), August [5]Nelson L. Max. Unified Sun and Sky Illumination for Shadows Under Trees. CVGIP: Graphical Models and Image Processing, 53(3): , May [6]S. Agarwal, R. Ramamoorthi, S. Belongie, and H. W.Jensen. Structured importance sampling of environment maps. ACM Trans. Graph., 22(3): , [7]P. Debevec. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. In Computer Graphics (ACM SIGGRAPH 98 Proceedings), pages , [8]T. Kollig and A. Keller. Efficient illumination by high dynamic range images. In Eurographics Symposium on Rendering, pages 45 51, [9]J. Thornegen, om sub_learn_typedissue asp?lv=3& ode=1 issue=002 References: [1]D. Renner, [2László Szécsi, Mateu Sbert, László Szirmay- Kalos,Combined Correlated and Importance Sampling in Direct Light Source Computation and Environment Mapping,Eurographics 2004,Volume 23, Number 3, [3]Y. Dobashi, K. Kaneda, H. Nakatani, and H. Yamashita.Method for Calculation of Sky Light Luminance Aiming at an Interactive Architectural Design. Computer Graphics Forum, :C109 C118, 1996.

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