Acquisition of CAD Data from Existing Buildings by Photogrammetry

Transcription

1 Acquisition of CAD Data from Existing Buildings by Photogrammetry Jörg Albertz Albert Wiedemann Technical University of Berlin, Berlin, Germany ABSTRACT: Data to be handled in CAD systems can either be defined interactively or it can be derived from existing construction plans. However, in many cases the real actual geometry of existing buildings is required. The task of surveying an existing building and the generation of a three-dimensional digital model is often referred to as»reverse engineering«. Photogrammetric methods offer very suitable solutions for this task. Compared to conventional methods of surveying, the acquisition of photogrammetric imagery is very fast and effective. The amount of information which is recorded in photographs surpasses each construction plan or drawing. The most important photogrammetric techniques are stereophotogrammetric restitution, bundle adjustment and generation of orthoimages. Digital image processing methods introduce a new era to photogrammetry, characterized by very high flexibility, semi-automated procedures and direct data transfer to CAD systems. Modern photogrammetry is a powerful means to acquire data from existing buildings for CAD purposes, both in vector formats and also in raster formats as orthoimages. 1 PRINCIPLES OF ARCHITECTURAL PHOTOGRAMMETRY For many purposes detailed plans of existing buildings are required. Especially for the preservation of architectural monuments a great variety of data about the facades and the structures is needed for documentation purposes and for planning of further activities, especially by CAD methods. If the original plans are not available or if the facade has been changed the only way to acquire this data is the survey of the buildings surface. This can be achieved either by direct measurements using scaffolding or indirectly by photogrammetric approaches. The basic idea of architectural photogrammetry is to reconstruct the imaging geometry which was effective during the exposure of photographs in order to derive object coordinates. However, the three dimensions of the object are reduced in the photograph to a two-dimensional image space. This is why three-dimensional object coordinates can not be derived from one image. Photogrammetry therefore combines informations from two appropriate images to survey a three-dimensional object. The photogrammetric approach offers several significant advantages compared to classical surveying methods. Field operations are reduced to the acquisition of photographs and the measurement of a few control points. In this way a tremendous amount of information is permanently stored in the photographic film, surpas- sing each construction plan or drawing. Any detail of a building, which is photographed in at least two images can be subject to photogrammetric restitution. This procedure can be carried out at any time and at any place independently from the object. Especially for the preservation of historical monuments the acquisition of photographs can serve the needs for documentation. In case of destruction or damage the images can be evaluated to get the required data for reconstruction. This aspect of setting up an archive of historical buldings was the main concern of Albrecht Meydenbauer in the 19th century and had a significant impact on the development of photogrammetry (Schwidefsky 1971). In the meantime the need to document and to preserve such monuments increased enormously (Waldhäusl 1992). Fortunately the photogrammetric techniques to solve such problems have developed step by step. Meydenbauer used graphical solutions, the stereophotogrammetric techniques made photogrammetry much more effective, the analytical approach more precise and bundle adjustment much more flexible. Currently the introduction of digital image processing opens up an new era of photogrammetry, where the measuring process can partly be automated and orthoimages as a new type of products in this field tend to become operational. Modern photogrammetry can effectively provide metric data of high and homogenous quality from existing buildings for CAD purposes.

2 2 STEREOPHOTOGRAMMETRIC RESTITUTION The conventional method of architectural photogrammetry is the stereophotogrammetric approach. The object is photographed with metric cameras, having a fixed focal length and fiducial marks on the calibrated frame, so that the imaging bundle of rays can be reconstructed. The images are taken in stereo pairs with approximately parallel axes. This simulates our stereoscopic view with two nearly parallel looking eyes. The traditional stereophotogrammetric approach requires a series of orientation procedures comprising the following three steps: Reconstruction of the bundle of rays of the camera by means of the calibration data (interior orientation). Determination of the relative position of the two images of a stereo pair (relative orientation). The result of this procedure is a three-dimensional model of the object. Transformation of the three-dimensional model into the coordinate system choosen for the project, making use of some control points (absolute orientation). Once this is concluded any point of the object can be determined in the three-dimensional coordinate system of the project by stereophotogrammetric measurements. Modern equipment for stereophotogrammetric restitution, operating fully computerized, is called Analytical Plotter (Fig.1). Such instruments consist of two photo carriers, visualiation optics with two oculars, control elements and of course computer processors. The operator observes the object stereoscopically and moves a floating mark through the three-dimensional model. The movement of the mark can be recorded in Fig.1: Analytical Plotter KERN DSR11 at the Department of Photogrammetry and Cartography, Technical University of Berlin Fig. 2: Photogrammetric acquisiton of data from existing buildings (schematic diagram). Through photogrammetry the threedimensional coordinates of relevant object points are determined. They can either be directly used for CAD purposes, projected onto a plane in order to derive facade plans, or used for the generation of orthoimages. the computer memory. The operator follows the edges and other structural lines of the building or picks up individual points. Thus a three-dimensional cluster of points resp. vectors is created, describing the geometrical structure of the building. The technical parameters can vary through a wide range. The amount of details and the accuracy as well are adjustable to the particular requirements. In many cases the object, e.g. the facade of a building, can not be recorded in one stereopair of images. Therefore it is necessary to combine the data of individual models to a complete data set. The diagram of Fig. 2 shows schematically the results of stereophotogrammetric data collection, Fig. 3 gives a practical example. The vector data recorded can be transferred to a CAD system. In general interactive editing work is required, especially to complete vector elements that have not been directly measured. Although the stereophotogrammetric approach is very effective and generally used, it implies some prac-

3 tical restrictions. Data acquisition is limited to stereo pairs and therefore often not flexible enough. An appropriate number and distribution of control points is required, the equipment is expensive, needs sophisticated calibration, and skilful operation. The methods of analytical photogrammetry are suited to overcome such limitations. 3 BUNDLE ADJUSTMENT The most important approach of analytical photogrammetry is the bundle adjustment. This technique reconstructs the geometric relations between an object point P(x i,y i,z i ) and its image P'(x' i,y' i ) by calculations, based on the collinearity equations. These equations describe the imaging process as a function of the parameters of the interior orientation (focal length c k and coordinates x' 0,y' 0 of the principal point) and the data of the exterior orientation (X 0,Y 0,Z 0,ω,ϕ and κ) of the image (Albertz et al. 1989): x' i x' 0 = c k a 11 (X i X 0 )+a 21 (Y i Y 0 ) a 31 (Z i Z 0 ) a 13 (X i X 0 )+a 23 (Y i Y 0 ) a 33 (Z i Z 0 ) y' i y' 0 = c k a 12 (X i X 0 )+a 22 (Y i Y 0 ) a 32 (Z i Z 0 ) a 13 (X i X 0 )+a 23 (Y i Y 0 ) a 33 (Z i Z 0 ) The rotation matrix is calculated as follows: a 11 a 12 a 13 R(ω,ϕ,κ ) = a 21 a 22 a 23 a 31 a 32 a 33 while a 11 = cos ϕ cos κ a 12 = cos ϕ sin κ a 13 = sin ϕ a 21 = cos ω sin κ + sin ω sin ϕ cos κ a 22 = cos ω cos κ sin ω sin ϕ sin κ a 23 = sin ω cos ϕ a 31 = sin ω sin κ cos ω sin ϕ cos κ a 32 = sin ω cos κ + cos ω sin ϕ sin κ a 33 = cos ω cos ϕ Using these equations for each point, i.e. for each pair of image coordinates, two observation equations can be set up. For each image 9 unknowns (6 for the exterior and 3 for the interior orientation) have to be determined. Any object point requires the determination of 3 unknowns. The whole system is treated according to the procedure of least squares adjustment, i.e. approximate values for the unknowns are defined, the observation equations are linearized, and the system of linear equations is solved by iterative calculations. This very general approach of bundle adjustment offers great flexibility and significant advantages compared to traditional stereophotogrammetry. The main m Fig. 3: Raw result of the stereophotogrammetric restitution of the southern wing of Nikolai Church at Jüterbog in Brandenburg aspects are: Photographs taken with any camera, also with non-metric cameras and different focal lengths, can be used for combined photogrammetric restitution. Photographs can be taken from any point of view in any direction, e.g. with convergent axis. The number of control points can be reduced to a minimum. The simultaneous overall adjustment of all bundles of rays in a project yields the highest accuracy which can be achieved. The only hardware required is a computer and the equipment for the measurement of image coordinates. This makes it independent of expensive instruments. The application of this approach, however, requires that certain conditions are considered: Each object point must be recorded in at least two images and the geometric configuration of the block of bundles involved must be such, that a proper solution of the equation system is possible. If these prerequisites are fulfilled, the approach can be successfully applied to very large blocks, formed by many images and a great num-

4 ber of object points, with altogether thousands of unknowns and many more observations. Three modifications of this bundle adjustment approach are of great practical importance: The control information to be introduced is not limited to the conventional type of control points. The mathematical model may be expanded in such a way, that distance measurements in the object space, height differences, informations about vertical lines, or other types of additional geometric data can be integrated in the calculations. This means will improve the accuracy of the results. It is also possible to refine the camera model, i.e. to define additional parameters in order to consider deviations from the central perspectivity described in the collinearity equations (distortions of the camera lens, unflatness of the image plane, etc.). In other words the interior orientation of the camera is improved by»self-calibration«. This means that the geometric accuracy of the results will increase, however, there are more unknowns to determine and this also requires a sufficient increase of the number of observations to be used in the adjustment. On the other hand the mathematical model can be simplified if the interior orientation data of the camera is provided from previous calibration. This corresponds to the conventional understanding of photogrammetry and such data is usually available for metric cameras. If this type of bundle adjustment is applied the number of observations resp. control points can be reduced. With the latter modification of the bundle approach we are back to the traditional instruments for acquisition of photogrammetric images. As already mentioned above, metric cameras are expensive and they provide only limited flexibility for architectural photogrammetry. This is why»semi-metric«cameras and PC-based systems for the photogrammetric restitution have been developed (Wester-Ebbinghaus 1983, Cogan et al. 1992). Such cameras copy reseau crosses on the film in order to control different types of distortion. This crosses are regularly distributed over the whole image (Fig. 4). Usually coordinates of the reseau crosses and of the object points are determined on a digitizer (or on a screen in case of scanned imagery). By comparing the measured positions of the crosses with precalibrated coordinates a correction function can be derived and applied in order to restitute the interior orientation of the image. For further processing identical object points in the images of a block of bundles as well as all available control points are digitized. The image coordinates of these points are the input information for a bundle adjustment. In this process the data of the exterior orientation for each image and three-dimensional coordinates of each object point measured in two or more images are calculated simultaneously. If the bundle adjustment approach is properly used it provides very high flexibility and offers a great potential of accuracy. Nevertheless, there is one disadvantage to be envisaged, namely the absence of stereoscopic effects. The bundle method is limited to Fig. 4: Photograph of the southern wing of the Nikolai Church, Jüterbog in Brandenburg: the image was taken with a semi-metric camera ROLLEIFLEX 6006 metric (focal length 50 mm) discrete object points,that can easily be identified in several images. In many practical cases this is fully sufficient, especially if the object is a more or less regularly shaped building as it can be discribed through points resp. vectors. However,in general these conditions can not be considered to be fulfilled. Most objects also show curved or irregularly shaped edges, stone joints or ruptures. In stereophotogrammetry the human operator interprets such elements and follows along with the floating mark, thus mapping these structures directly. In order to achieve similar results in combination with the bundle approach digital image processing together with computer vision techniques must be applied. 4 DIGITAL PHOTOGRAMMETRY The photogrammetric techniques discussed so far make use of analog data, i.e. measurements are taken from photographic images. Since digital image processing became such a powerful tool, it was possible to envisage a new generation of photogrammetric systems,

5 where measurements are carried out in digital image data. The fully digital approach to photogrammetry provides not only a great variety of practical advantages but also the chance to automate measuring processes. Years ago it was already evident, that this development will also have an enormous impact on close range photogrammetry (Albertz 1986). The basic data flow of digital photogrammetry is outlined in the diagram of Fig. 5. The image data to be processed can either be digitized from photographs of a film camera or they can be acquired directly in digital formats, e.g. by means of a CCD camera. Then the digital image data can of course be subject to all kinds of processing such as contrast enhancement, filtering, correction of geometric or radiometric distortions etc. The data can be displayed on a stereo monitor, i.e. the human operator can work in a similar way as it is done in an analytical plotter, and also bundle adjustments can be carried out. But the most important innovations are the following aspects: The identification of homologous points in two or more images can automatically be achieved by digital matching techniques; in other words it is not longer necessary, that time-consuming and tedious routine measurements are conducted by a human operator. If certain requirements are Fig. 5: Schematic diagram of the data flow from the object to the CAD sytem if digital photogrammetry is applied met, digital image matching techniques operate very well and effectively. Different types of computer vision approaches allow in principle the automatic extraction of segments, edges, points of special interest or other features in the image data. In other words, the interpretation of images, which is so far the task of the human operator, will at least partly be carried out by computer programs. It is due to these aspects that digital photogrammetric workstations can be understood as a combination of three different approaches for evaluating image data. The first approach is very similar to the conventional one: The human operator uses the enormous potential of his eye-brain-system to process the image data displayed on the monitor simultaneously. He conducts complex image analysis on a very high level, recognizes object feature, selects relevant points and object structures, etc, and he also carries out measurements. To measure means in this case, that he defines 3D object coordinates, the defined point is digitally projected to the images (collinearity equations), and this procedure is repeated interactively until the operator sees the floating mark in correspondance with the relevant object feature. Thus a feedback loop is established (dashed lines in Fig. 5) which is typical for this procedure. The second approach is quite different: Homologous points, i.e. image points corresponding to the same object point, are determined by digital image matching techniques. This method makes use of structural properties of the image data without interpretation or semantic information. The approach is well developed and operates effectively if the image structures are appropriate and without ambiguities. From the resulting image coordinates the 3D object coordinates of the particular point are determined through digital projection (collinearity equations in inverse form). Unlike the first approach, there is no feedback loop involved. Systems of this type are known as»digital Photogrammetric Workstations«. They look very similar to general workstations (Fig. 6), however, they are equipped with a stereo monitor and an input device for three coordinates. Digital photogrammetric workstations combine different approaches to image evaluation: The human operator has an enormous potential in evaluating images and doing semantic interpretation, making use of his experience and background knowledge and also having in mind the purpose of the task. On the other hand, the computer has an enormous capacity to carry out numerical calculations at high speeds and to process large amounts of digital data with full accuracy. If man and machine work together (»job-sharing«) each one conducts what he does best, and the whole system becomes optimized. Thus the photogrammetric operator can be relieved from tiresome and time-consuming routine work and concen-

6 trate on image interpretation and visual control of the computer results. The third aspect is to make use of computer vision techniques and to introduce also some automatic interpretation features in the systems software (this not explicitly sketched in the diagram of Fig. 5). Sometimes fashionable terms, like»artificial Intelligence«, are used in this context. However, despite a lot of research activities in computer vision, the practical Fig. 6: Digital photogrammetric workstation ZEISS Phodis ST Through digital image processing also the production of orthoimages of buildings becomes feasible. This is desirable, because each photogrammetrically derived plan is the result of an interpretation process, where the complex image information is reduced to some simple lines. This enormous reduction of information can be avoided by preparing orthoimages. Orthoimages are orthogonal projections of threedimensional objects on a mathematically defined surface. Usually the selected surface is a plane, thus the orthogonal projection becomes parallel. The traditional approach for the generation of orthophotos is to cut down the original perspective image into small elements and to locate these elements properly in a new image according to the parallel projection. The resulting image has the geometrical properties of a plan or a map. It allows the direct measurement of distances, areas, directions etc. On the other hand the structural informations of the image are still available for further interpretation. A user may interpret the image data according to his own requirements and perhaps update the results of photogrammetric evaluation. This is why orthoimages can also avoid misunderstandings beapplications are not yet developed. So far, the automatic interpretation of the detected elements is limited to rather simple tasks. The automatic attachment of corresponding features in several images seems to be attainable within the near future. But there are still a lot of problems to be solved. It should be noted, that the appearance of an object in two pictures is very similar if the images have been taken with parallel axes and a relatively short distance between the points of view. But convergent architectural images show an object in very different ways. Hidden lines and surfaces complicate topological approaches for the attachment. Differences in the illumination cause problems in the use of radiometric data for this purpose. Repeated similar structures may produce mismatches. Unfortunately the real world is much more complex than computer vision likes to have it. Therefore a great amount of further research will be necessary in order to develop operational methods. Also with regard to feature extraction and other computer vision tasks, there are good chances that interactive techniques yield reliable results and work more effectively than automated approaches. This is why semi-automated systems are subject to actual research and development, where the human operator selects the image features to be measured, whereas the computer conducts the definition of points or vectors by numerical caluculations (e.g. Nonin 1992, Streilein 1994). Recently the first commercial Digital Photogrammetric Workstations became available on the market (Miller et al. 1995, Willkomm et al. 1995, Frick 1995). Such systems are primarily designed for mapping purposes, i.e. for processing aerial photographs. They seem to be not well suited for use in architectural surveys. In most cases they are developed as analytical plotters with stereo monitors instead of two oculars. So far the only digital image processing approach widely used is image matching. It yields good results and operates effectively if a continuous surface is concerned, the surface texture is sufficient and the images are taken with nearly parallel axes. These prerequisites are generally not met in architectural photogrammetry. This is why the commercially available systems need some specific upgrades considering the typical structures of buildings and the great flexibility in data acquisition as well. Nevertheless, it can be foreseen, that image matching techniques will also become operational for the survey of buildings in the near future The integration of a digital photogrammetric workstation with a CAD program is a relatively easy task. It may be very helpful, especially in order to reduce the necessity to revise data. Furthermore, it should also be mentioned, that in digital photogrammetric workstations image data and vector data can easily be combined. It is quite common to overlay existing or derived vector information over the raster image data, thus providing excellent possibilities for control and assessment of the CAD data. 5 ORTHOIMAGES

7 tween the photogrammetric operator and the user of the acquired CAD data. In the fields of topographic mapping, regional planning etc. orthoimages are widely used since decades. There has also been significant research work in preparing orthoimages from architectural objects by conventional orthophoto techniques (Seeger 1979, Vozikis 1979). The basic idea is to project not only the graphical data but also the image data onto a plane as it is schematically shown in Fig. 2. But a breakthrough with regard to practical applications could not be achieved. One reason for the limited acceptance of orthoimages from buildings may be that architects, archeologists etc. are just unfamiliar with this type of product. But due to the inflexibility of the conventional orthophoto systems and especially the geometrically complex structure of buildings, there have also been drastic limitations in the generation of orthoimages. These limitations can be overcome if digital image processing is consequently applied. The pixel structure of a digitized image is ideally suited for differential rectification in order to generate a digitized orthoimage. For each pixel of the final image the object distance over the projection plane is derived from a Digital Object Model (DOM). By using the collinearity equations the position of the surface element in the original image can be calculated. Then the gray value of the original image at this position is transferred to the proper pixel of the orthoimage. The determination of the parameters for the collinearity equations is not difficult, it can be achieved by resection in space, in an analytical plotter or by bundle adjustment. However, the bottle-neck of the approach is the exact geometric description of the object's surface in the DOM. In topographic sciences the surface is provided in the form of a Digital Terrain Model, i.e. a set of data given in a regular grid describing the elevations of the terrain's surface over a particular plane. The necessary input data can be derived from the results of photogrammetric restitution of stereo images. The elevations of the grid points have to be interpolated out of the irregularly distributed primary data by appropriate methods. Interpolation programs are generally available and yield excellent results for continuous surfaces, for example in the topography. However, the geometrical structure of buildings is characterized by many discontinuities. This is why the facade of a building cannot suitably be handled by such software systems. More sophisticated data models, considering the geometrical conditions of buildings, are necessary. There have already attempts been made to realize orthoimage generation from buildings by digital image processing techniques, and some interesting results were reported (Marten et al. 1994). But a lot of further development is necessary, especially in order to achieve the flexibility which is required for this task. 5 CONCLUSIONS Following the general technological development photogrammetry has been more and more converted from analogue to digital procedures. Each step in this development was closely associated with a higher degree of flexibility and improvements of the quality of the results. This is why modern photogrammetry is a powerful tool for»reverse engineering«, i.e. for the acquisition of geometric data from existing buildings for CAD purposes. However, the progress is not only restricted to geometric data. Digital image processing techniques make it possible to convert normal images to orthoimages. This product type has the same geometric properties as a plan, but it preserves the detailed image information which is available in a black-and-white or color image. This development is currently in an experimental stage, but it is easy to predict, that orthoimages from buildings will become a standard product in the future. Furthermore, photogrammetric processing of image data will more and more benefit from the development of computer vision methods. There are great chances to replace most of the tedious routine measuring work of an operator by automatic procedures, thus allowing the experienced human operator to concentrate on what he does best, i.e. the interpretation of object details out of images. Architectural photogrammetry looks back to a very long tradition. But thanks to modern technological developments also a fascinating future can be anticipated. REFERENCES Albertz, J Digitale Bildverarbeitung in der Nahphotogrammetrie Neue Möglichkeiten und Aufgaben. 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