A COMPARISON OF SPARSE AND DENSE POINT APPROACH TO PHOTOGRAMMETRIC 3D MODELING FOR STONE TEXTURED OBJECTS (CASE STUDY: ARCHEOLOGICAL SITES) Arnadi D. Murtiyoso 1, Deni Suwardhi 2 1,2 Spatial Information Systems and Technologies Laboratory Bandung Institute of Technology LabTek IXC 3 rd Floor, Jalan Ganesa 12, Bandung 40132 INDONESIA E-mail: 1 murtiyoso.arnadi@gmail.com, 2 deni@gd.itb.ac.id ABSTRACT Three dimensional (3D) modeling has been an important process in documenting archeological sites. Unlike conventional 2D drawings, 3D models provide both archeologists and future reconstruction workers with accurate geometrical data of the object in digital form, thus enabling various experiments and research. For this cause, archeological institutions usually employ either the terrestrial laser scanner, or cameras using photogrammetric techniques. Photogrammetric techniques are usually employed due to their relatively low cost, simple equipments, and quick data acquisition. Photographs can then be processed into sparse point 3D model. However, with the introduction of advanced image matching algorithms, this technique can also generate dense point clouds similar to results from laser scanners. A prerequisite for this technique however, requires that the object in question possesses a texture with patterns in order to allow automatic image markings. In nature, stone textures in general provide a perfect example of this requirement. Dense point cloud generation is very useful especially to model intricate architectural details from objects such as roofs and reliefs. This has been done to document shrine No. 72, Sewu Temple Complex in Central Java, Indonesia. The purpose of this research is to determine whether the dense point approach is more effective and generates an altogether better result when compared to the sparse point approach when used to model a stone structure which is less intricate. In this case, Cangkuang Temple in West Java was chosen. Cangkuang Temple, unlike Sewu Temple, does not have intricate reliefs, but is still adorned with a tiered roof which can be time-consuming when modeled using the sparse point approach to achieve the same level of detail with dense point results. On the other hand, wherever possible, sparse point approach can minimize noise and holes on the 3D model prevalent when creating dense point models. Keywords: archeology, close range photogrammetry, dense point, sparse point 1
1. Introduction Conventional archeological documentation includes either or both the drawing of the object s façade or its cross-sectionals and taking photographs (Harintaka, Subaryono, & Octapianus, 2008). This provides archeologists with a two-dimensional perspective of the archeological object; with scales attached, spatial information can also be extracted. However, in today s largely digital environment, a 2D drawing does not give room for modeling and manipulating of the data. In this case, a 3D model representation is preferred. Furthermore, 3D representation of archeological objects can help archeologists to interpret, document, as well as interactively providing people with archeological information. The International Conference on Culture and Tourism strongly recommends the use of information technology and the internet to develop cultural tourism around archeological objects (Riyanto, 2006). The use of terrestrial laser scanners (TLS) can indeed hasten the process of 3D modeling, however Behan & Moss (2006) argues that for many individuals and organizations concerned with the preservation and research of cultural heritage, the TLS provides an unrealistic solution. This is due mainly to two factors, funding and the required knowledge. Behan & Moss (2006) concluded that TLS can only be used for projects with large funding. Close range photogrammetry is an alternative technique which can also be applied for that purpose. Harintaka, Subaryono, & Octapianus (2008) mentions that some of the main advantages of using non-metric cameras in virtual reconstructions are the low cost instruments, good radiometric resolution, and improving spatial resolution. Sewu Temple is a complex of Buddhist temples and shrines located in Central Java and estimated to have been built in the 8 th century A.D. After a long period of abandonment, it was rediscovered in the early 19 th century and drawn by H. C. Cornelius (Dumarçay, 1986). However, the temple remains in a state of almost entirely in ruins, and has since been preserved and reconstructed. The façades of some of the shrines remains in a good condition, such as the ones on Shrine No.72, which is the object of study in this research. Cangkuang Temple, on the other hand, is an individual Hindu temple also dating from the 8 th century A.D. It is located near the city of Garut, West Java, and is the only Hindu temple found in West Java. It was discovered in a state of near complete ruin. Restoration work does not try to reimagine carvings on the façade, and therefore this temple s façades does not have intricate reliefs as Sewu Temple does. 2
(a) (b) Figure 1 (a) Shrine no 72, Sewu Temple Complex and (b) Cangkuang Temple. Notice the intricate reliefs on Figure 1(a) and the lack of it on Figure 1(b) In close range photogrammetry, sparse point modeling is essentially a digitizing process on the oriented photos. This method of 3D modeling is simple and quick to utilize; however it is difficult and even in some cases impossible to model intricate carvings. Dense point modeling on the other hand, employs automatic image matching algorithms to compute the 3D coordinates of thousands of points from a pair of oriented photos. A prerequisite for this technique however, requires that the object in question possesses a texture with patterns in order to allow automatic image markings. In nature, stone textures in general provide a perfect example of this requirement. This modeling method is easier to employ as it requires minimal operator involvement, but can result in large amount of noises and gaps and data processing can take up a lot of time depending on the hardware capabilities. However, as reliefs and carvings are impossible to be modeled by the sparse point method, the dense point method is very useful to fulfill these needs. Sparse point modeling has been successfully employed on several archeological reconstruction projects such as the documentation of Monastery of Christ Pantepoptes by Duran & Toz (2002), and the historical church of Derinkuyu Kilisesi by Yildiz et al. (2010) in Turkey. On the other hand, dense point modeling was employed on the documentation of My Son Temple in Vietnam by Barazzetti et al. (2009). The purpose of this study is to compare the use of dense point modeling for objects with reliefs; in this case Shrine No.72 in Sewu Temple Complex was used, and for objects without reliefs; in this case Cangkuang Temple was used. A sparse point modeling of Sewu Temple Shrine No.72 will also be used as a comparison of visual results. 3
2. Methodology For the purposes of this research, a close range photogrammetic software, PhotoModeller Scanner was used. This software has the capability of doing dense point modeling by means of an automated image matching algorithm, followed by space intersection of the respective points to acquire their 3D coordinates. The camera used for the purpose of this study is a Nikon D5000 DSLR camera with a fixed focal length of 24 mm. Camera calibration was done by photographing a calibration grid on an iron plate from several angles. The resulting photographs were then processed using Australis 7. For this phase, Australis is preferred than Photomodeler as it is more scientific and provides a more robust calculation. This is demonstrated by the resulting calibration parameters where Photomodeler tends to be more unstable for the same camera. On the other hand, Australis showed a better and more stable performance in the calculation of calibration parameters. However, Australis lacks the image matching feature for dense surfaces generation of PhotomodelerScanner. It also lacks some features to draw primitive graphs. Therefore, the calibration parameters from Australis s calculation was then used for further data processing in Photomodeler. Data acquisition was done by taking photographs in a convergent manner around the object. About 16 photos were used for the reconstruction of Sewu Shrine, and about 12 for Cangkuang Temple. From these photos, sparse and dense point models of the respective objects were built using Photomodeler Scanner. 3. Results and Analysis As can be seen from Figure 1a a sparse point modeling of Sewu Shrine is possible to do for some of its features such as the tiered dais and roof. However, the reliefs on the façade were unfortunately modeled as a flat surface. Also the stupa is difficult to model as there are no primitive graph tools in Photomodeler which can be used to satisfactorily create the stupa. 4
(a) (b) (c) Figure 2 (a) sparse point and (b) dense point models of Sewu Shrine; (c) shows the closeup of the relief s 3D model In Figure 2c it can be seen that the dense point modeling was successful in creating a good representation of the reliefs, albeit with some gaps. These relatively small gaps, however, can be eliminated by means of surface interpolation in further processing. On the stupa (Figure 2b) it can also be seen that the technique managed to create the dome structure, but with a large part of it missing in gaps. This is due to the lack of photographs concentrating on the stupa. A possible solution to this problem is the use of unmanned aerial vehicles to take photographs from the otherwise inaccessible angles by means of terrestrial photography. In the dense point model of the Cangkuang Temple (Figure 3a), the façades were adequately modeled, but still with the same problem of gaps. The resulting model shows that the nearly 5
flat surface of the walls were also modeled almost flat by the dense point method (Figure 3b), which shows that this method generates a good accuracy. However, the roof of the temple which is tiered shows a great amount of noises. This tiered roof would have been tedious to be modeled using the sparse point method, but it would have resulted in a noiseless result. Using the dense point method, the computer detects the surrounding patterns as points in addition to the intended points of the temple s roof. These surrounding patterns can be in the form of leaves, dirt, or other stone structures. As can be seen in this case, the temple which is located in a forest becomes a disadvantage for the dense point method. (a) (b) Figure 3 (a) 3D dense point model of Cangkuang Temple s front façade and (b) a close up of the façade s walls 4. Conclusion With the advent of advanced image matching algorithm, sparse point modeling where an operator s work is enormous seems to be inferior to the dense point modeling method, where the work of the operator can be minimized as much of the work is done by computers. However, results from this research shows that while today s dense point generation algorithm can produce results with adequate accuracy, it is still bugged by the problems of gaps and noises. Most gaps and noises can be reduced in further processing of the 3D model, however this again requires the work of an operator. By comparing methods from both Sewu Shrine and Cangkuang Temple, we can conclude that dense point method can be used for both façades with intricate carvings or plain wall. In cases where the surrounding area of the object is clear, as in the case of Sewu Shrine, dense point method can be used to substitute for the conventional sparse point method. However, as 6
can be seen in the case of Cangkuang Temple, the surrounding area proves to be very important in dense point modeling. Cangkuang Temple is surrounded by trees, and patterns on the leaves often confuse the image matching algorithm of the software, resulting in a large number of noises. This can be minimized by a careful trimming of the matching area, but as the research showed, noises are still present. In cases where the model s noises are too many and the object is simple enough, a sparse point modeling would be a better choice. 7
Arnadi Dhestaratri Murtiyoso is a research assistant at Spatial Information Systems and Technologies (SISTECH) Laboratory, Bandung Institute of Technology (ITB). He graduated from Geodesy and Geomatics Engineering, ITB in 2011 and is currently working on some researches involving close range photogrammetry, both terrestrial and aerial. His primary fields of interest include close range photogrammetry, medieval history, and archeology. He has worked on several studies including the virtual reconstruction of Shrine No.72, Sewu Temple Complex in collaboration with Yogyakarta Archeological Bureau. Contact: Spatial Information Systems and Technologies Laboratory Bandung Institute of Technology LabTek IXC 3 rd Floor, Jalan Ganesa 12, Bandung 40132 INDONESIA Mobile:+6281322841922 Fax:+62222501116 E-mail:murtiyoso.arnadi@gmail.com 8