Maarten Vergauwen

Visual Modeling with a Hand-Held Camera

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.

Web-based 3D Reconstruction Service

The use of 3D information in the field of cultural heritage is increasing year by year. From this field comes a large demand for cheaper and more flexible ways of 3D reconstruction. This paper describes a web-based 3D reconstruction service, developed to relieve those needs of the cultural heritage field. This service consists of a pipeline that starts with the user uploading images of an object or scene(s) he wants to reconstruct in 3D. The automatic reconstruction process, running on a server connected to a cluster of computers, computes the camera calibration, as well as dense depth (or range-) maps for the images. This result can be downloaded from an ftp server and visualized with a specific tool running on the user’s PC.

Automated reconstruction of 3D scenes from sequences of images

Modelling of 3D objects from image sequences is a challenging problem and has been an important research topic in the areas of photogrammetry and computer vision for many years. In this paper, a system is presented which automatically extracts a textured 3D surface model from a sequence of images of a scene. The system can deal with unknown camera settings. In addition, the parameters of this camera are allowed to change during acquisition (e.g., by zooming or focusing). No prior knowledge about the scene is necessary to build the 3D models. Therefore, this system offers a high degree of flexibility. The system is based on state-of-the-art algorithms recently developed in computer vision. The 3D modelling task is decomposed into a number of successive steps. Gradually, more knowledge of the scene and the camera setup is retrieved. At this point, the obtained accuracy is not yet at the level required for most metrology applications, but the visual quality is very convincing. This system has been applied to a number of applications in archaeology. The Roman site of Sagalassos (southwest Turkey) was used as a test case to illustrate the potential of this new approach.

A Hierarchical Symmetric Stereo Algorithm Using Dynamic Programming

In this paper, a new hierarchical stereo algorithm is presented. The algorithm matches individual pixels in corresponding scanlines by minimizing a cost function. Several cost functions are compared. The algorithm achieves a tremendous gain in speed and memory requirements by implementing it hierarchically. The images are downsampled an optimal number of times and the disparity map of a lower level is used as ‘offset’ disparity map at a higher level. An important contribution consists of the complexity analysis of the algorithm. It is shown that this complexity is independent of the disparityrange. This result is also used to determine the optimal number of downsample levels. This speed gain results in the ability to use more complex (compute intensive) cost functions that deliver high quality disparity maps. Another advantage of this algorithm is that cost functions can be chosen independent of the optimisation algorithm. The algorithm in this paper is symmetric, i.e. exactly the same matches are found if left and right image are swapped. Finally, the algorithm was carefully implemented so that a minimal amount of memory is used. It has proven its efficiency on large images with a high disparity range as well as its quality. Examples are given in this paper.

Metric 3D Surface Reconstruction from Uncalibrated Image Sequences

Modeling of 3D objects from image sequences is one of the challenging problems in computer vision and has been a research topic for many years. Important theoretical and algorithmic results were achieved that allow to extract even complex 3D scene models from images. One recent effort has been to reduce the amount of calibration and to avoid restrictions on the camera motion. In this contribution an approach is described which achieves this goal by combining state-of-the-art algorithms for uncalibrated projective reconstruction, self-calibration and dense correspondence matching.

Hand-held acquisition of 3D models with a video camera

Modeling of 3D objects from image sequences is a challenging problem and has been a research topic for many years. Important theoretical and algorithmic results were achieved that allow to extract even complex 3D scene models from images. One recent effort has been to reduce the amount of calibration and to avoid restrictions on the camera motion. In this contribution an approach is described which achieves this goal by combining state-of-the-art algorithms for uncalibrated projective reconstruction, self-calibration and dense correspondence matching.

A Stereo Vision System for Support of Planetary Surface Exploration

In this paper a system will be presented that was developed for ESA for the support of planetary exploration. The system that is sent to the planetary surface consists of a rover and a lander. The lander contains a stereo head equipped with a pan-tilt mechanism. This vision system is used both for modeling of the terrain and for localization of the rover. Both tasks are necessary for the navigation of the rover. Due to the stress that occurs during the flight a recalibration of the stereo vision system is required once it is deployed on the planet. Due to practical limitations it is infeasible to use a known calibration pattern for this purpose and therefore a new calibration procedure had to be developed that can work on images of the planetary environment. This automatic procedure recovers the relative orientation of the cameras and the pan-and tilt-axis, besides the exterior orientation for all the images. The same images are subsequently used to recover the 3D structure of the terrain. For this purpose a dense stereo matching algorithm is used that - after rectification - computes a disparity map. Finally, all the disparity maps are merged into a single digital terrain model. In this paper a simple and elegant procedure is proposed that achieves that goal. The fact that the same images can be used for both calibration and 3D reconstruction is important since in general the communication bandwidth is very limited. In addition to the use for navigation and path planning, the 3D model of the terrain is also used for Virtual Reality simulation of the mission, in which case the model is texture mapped with the original images. The system has been implemented and the first tests on the ESA planetary terrain testbed were successful.

3D recording for archaeological fieldwork

Until recently, archaeologists have had limited 3D recording options because of the complexity and expense of the necessary recording equipment. We outline a system that helps archaeologists acquire 3D models without using equipment more complex or delicate than a standard digital camera.

Three-dimensional scene reconstruction from images

Modeling of 3D objects from image sequences is a challenging problem and has been a research topic for many years. Important theoretical and algorithmic results were achieved that allow to extract even complex 3D models of scenes from sequences of images. One recent effort has been to reduce the amount of calibration and to avoid restrictions on the camera motion. In this contribution an approach is described which achieves this gaol by coming state-of-the-art algorithms for uncalibrated projective reconstruction, self- calibration and dense correspondence matching.

Image-based 3D acquisition of archaeological heritage and applications

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.