In this paper a complete system to build visual models from camera images is presented. The system can deal with uncalibrated image sequences acquired with a hand-held camera. Based on tracked or matched features the relations between multiple views are computed. From this both the structure of the scene and the motion of the camera are retrieved. The ambiguity on the reconstruction is restricted from projective to metric through self-calibration. A flexible multi-view stereo matching scheme is used to obtain a dense estimation of the surface geometry. From the computed data different types of visual models are constructed. Besides the traditional geometry- and image-based approaches, a combined approach with view-dependent geometry and texture is presented. As an application fusion of real and virtual scenes is also shown.

n archaeology, measurement and documentation are both important, not only to record endangered archaeological sites, but also to record the excavation process itself. Annotation and precise documentation are important because evidence is actually destroyed during archaeological work. On most sites, archaeologists spend a large amount of time drawing plans, making notes, and taking photographs. Because of the publicity that accompanied some recent archaeological research projects , such as Stanford's Digital Michelangelo project 1 or IBM's Pieta project, 2 archaeologists are becoming aware of the advantages of using 3D visualization tools. Archaeologists can now use the data recorded during excavations to generate virtual 3D models suited for project report presentation, restoration planning, or even digital archiving, although many issues remain unresolved. Until recently, the cost in time and money to generate virtual reconstructions remained prohibitive for most archaeological projects. At a more modest level, some archaeologists use commercially available software, such as PhotoModeler (http://www.photo-modeler.com), to build simple virtual models. These models can suffice for some types of presentations, but typically lack the detail and accuracy needed for most scientific applications. Clearly, archaeologists need more flexible measurement techniques, especially for fieldwork. Archaeologists should be able to acquire their own measurements simply and easily. Our image-based 3D recording approach offers several possibilities. 3-8 To acquire a 3D reconstruction, our system lets archaeologists take several pictures from different viewpoints using a standard photo or video camera. In principle, using our system means that archaeologists need not take additional measurements of the scene to obtain a 3D model. However, a reference length can help in obtaining the recon-struction's global scale. Archaeologists can use the resulting 3D model for measurement and visualization purposes. Figure 1 shows an example of the types of pictures possible with a standard camera. In developing our system, we regularly visited Sagalassos, a site that is one of the largest archaeological projects in the Mediterranean. The site consists of elements from a Greco-Roman period spanning more than a thousand years from the 4th century BC to the 7th century AD. Sagalassos, one of the three great cities of ancient Pisidia, lies a few miles north of the village Aglassun in the province of Burdur, Turkey. The ruins of the city lie on the southern flank of the Aglassun mountain ridge (a part of the Taurus mountains) at an elevation of several thousand feet. Figure 2 shows Sagalassos against the mountains. A team …

In this contribution we intend to present a complete system that takes a video sequence of a static scene as input and outputs a 3D model. The system can deal with images acquired by an uncalibrated hand-held camera, with intrinsic camera parameters possibly varying during the acquisition. In a (cid:2)st stage features are extracted and tracked throughout the sequence. Using robust statistics and multiple view relations the 3D structure of the observed features and the camera motion and calibration are computed. In a second stage stereo matching is used to obtain a detailed estimate of the geometry of the observed scene. The presented approach integrates state-of-the-art algorithms developed in computer vision, computer graphics and photogrammetry.

In this paper an approach is presented that obtains virtual models from sequences of images. The system can deal with uncalibrated image sequences acquired with a hand-held camera. Based on tracked or matched features the relations between multiple views are computed. From this both the structure of the scene and the motion of the camera are retrieved. The ambiguity on the reconstruction is restricted from projective to metric through auto-calibration. A flexible multi-view stereo matching scheme is used to obtain a dense estimation of the surface geometry. From the computed data virtual models can be constructed or, inversely, virtual models can be included in the original images.

In this paper an approach is presented that obtains virtual models from sequences of images. The system can deal with uncalibrated image sequences acquired with a hand held camera. Based on tracked or matched features the relations between multiple views are computed. From this both the structure of the scene and the motion of the camera are retrieved. The ambiguity on the reconstruction is restricted from projective to metric through auto-calibration. A flexible multi-view stereo matching scheme is used to obtain a dense estimation of the surface geometry. From the computed data virtual models can be constructed or, inversely, virtual models can be included in the original images.

In this paper an approach is presented that obtains virtual models from sequences of images. The system can deal with uncalibrated image sequences acquired with a hand-held camera. Based on tracked or matched features the relations between multiple views are computed. From this both the structure of the scene and the motion of the camera are retrieved. The ambiguity on the reconstruction is restricted from projective to metric through auto-calibration. A flexible multi-view stereo matching scheme is used to obtain a dense estimation of the surface geometry. From the computed data virtual models can be constructed or, inversely, virtual models can be included in the original images.