Automatic extraction of Manhattan-World building masses from 3D laser range scans.

We propose a novel approach for the reconstruction of urban structures from 3D point clouds with an assumption of Manhattan World (MW) building geometry; i.e., the predominance of three mutually orthogonal directions in the scene. Our approach works in two steps. First, the input points are classified according to the MW assumption into four local shape types: walls, edges, corners, and edge corners. The classified points are organized into a connected set of clusters from which a volume description is extracted. The MW assumption allows us to robustly identify the fundamental shape types, describe the volumes within the bounding box, and reconstruct visible and occluded parts of the sampled structure. We show results of our reconstruction that has been applied to several synthetic and real-world 3D point data sets of various densities and from multiple viewpoints. Our method automatically reconstructs 3D building models from up to 10 million points in 10 to 60 seconds.

Pose-free structure from motion using depth from motion constraints.

Structure from motion (SFM) is the problem of recovering the geometry of a scene from a stream of images taken from unknown viewpoints. One popular approach to estimate the geometry of a scene is to track scene features on several images and reconstruct their position in 3-D. During this process, the unknown camera pose must also be recovered. Unfortunately, recovering the pose can be an ill-conditioned problem which, in turn, can make the SFM problem difficult to solve accurately. We propose an alternative formulation of the SFM problem with fixed internal camera parameters known a priori. In this formulation, obtained by algebraic variable elimination, the external camera pose parameters do not appear. As a result, the problem is better conditioned in addition to involving much fewer variables. Variable elimination is done in three steps. First, we take the standard SFM equations in projective coordinates and eliminate the camera orientations from the equations. We then further eliminate the camera center positions. Finally, we also eliminate all 3-D point positions coordinates, except for their depths with respect to the camera center, thus obtaining a set of simple polynomial equations of degree two and three. We show that, when there are merely a few points and pictures, these "depth-only equations" can be solved in a global fashion using homotopy methods. We also show that, in general, these same equations can be used to formulate a pose-free cost function to refine SFM solutions in a way that is more accurate than by minimizing the total reprojection error, as done when using the bundle adjustment method. The generalization of our approach to the case of varying internal camera parameters is briefly discussed.

Projector placement planning for high quality visualizations on real-world colored objects.

Many visualization applications benefit from displaying content on real-world objects rather than on a traditional display (e.g., a monitor). This type of visualization display is achieved by projecting precisely controlled illumination from multiple projectors onto the real-world colored objects. For such a task, the placement of the projectors is critical in assuring that the desired visualization is possible. Using ad hoc projector placement may cause some appearances to suffer from color shifting due to insufficient projector light radiance being exposed onto the physical surface. This leads to an incorrect appearance and ultimately to a false and potentially misleading visualization. In this paper, we present a framework to discover the optimal position and orientation of the projectors for such projection-based visualization displays. An optimal projector placement should be able to achieve the desired visualization with minimal projector light radiance. When determining optimal projector placement, object visibility, surface reflectance properties, and projector-surface distance and orientation need to be considered. We first formalize a theory for appearance editing image formation and construct a constrained linear system of equations that express when a desired novel appearance or visualization is possible given a geometric and surface reflectance model of the physical surface. Then, we show how to apply this constrained system in an adaptive search to efficiently discover the optimal projector placement which achieves the desired appearance. Constraints can be imposed on the maximum radiance allowed by the projectors and the projectors' placement to support specific goals of various visualization applications. We perform several real-world and simulated appearance edits and visualizations to demonstrate the improvement obtained by our discovered projector placement over ad hoc projector placement.

Modeling repetitive motions using structured light.

Obtaining models of dynamic 3D objects is an important part of content generation for computer graphics. Numerous methods have been extended from static scenarios to model dynamic scenes. If the states or poses of the dynamic object repeat often during a sequence (but not necessarily periodically), we call such a repetitive motion. There are many objects, such as toys, machines, and humans, undergoing repetitive motions. Our key observation is that when a motion-state repeats, we can sample the scene under the same motion state again but using a different set of parameters; thus, providing more information of each motion state. This enables robustly acquiring dense 3D information difficult for objects with repetitive motions using only simple hardware. After the motion sequence, we group temporally disjoint observations of the same motion state together and produce a smooth space-time reconstruction of the scene. Effectively, the dynamic scene modeling problem is converted to a series of static scene reconstructions, which are easier to tackle. The varying sampling parameters can be, for example, structured-light patterns, illumination directions, and viewpoints resulting in different modeling techniques. Based on this observation, we present an image-based motion-state framework and demonstrate our paradigm using either a synchronized or an unsynchronized structured-light acquisition method.

A self-calibrating method for photogeometric acquisition of 3D objects.

We present a self-calibrating photogeometric method using only off--the-shelf hardware that enables quickly and robustly obtaining multimillion point-sampled and colored models of real-world objects. Some previous efforts use a priori calibrated systems to separately acquire geometric and photometric information. Our key enabling observation is that a digital projector can be simultaneously used as either an active light source or as a virtual camera (as opposed to a digital camera, which cannot be used for both). We present our self--calibrating and multiviewpoint 3D acquisition method, based on structured light, which simultaneously obtains mutually registered surface position and surface normal information and produces a single high-quality model. Acquisition processing freely alternates between using a geometric setup and using a photometric setup with the same hardware configuration. Further, our approach generates reconstructions at the resolution of the camera and not only the projector. We show the results of capturing several high-quality models of real--world objects.

Visualization of simulated urban spaces: inferring parameterized generation of streets, parcels, and aerial imagery.

Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout and produce a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle.

An adaptive correspondence algorithm for modeling scenes with strong interreflections.

Modeling real-world scenes, beyond diffuse objects, plays an important role in computer graphics, virtual reality, and other commercial applications. One active approach is projecting binary patterns in order to obtain correspondence and reconstruct a densely sampled 3D model. In such structured-light systems, determining whether a pixel is directly illuminated by the projector is essential to decoding the patterns. When a scene has abundant indirect light, this process is especially difficult. In this paper, we present a robust pixel classification algorithm for this purpose. Our method correctly establishes the lower and upper bounds of the possible intensity values of an illuminated pixel and of a non-illuminated pixel. Based on the two intervals, our method classifies a pixel by determining whether its intensity is within one interval but not in the other. Our method performs better than standard method due to the fact that it avoids gross errors during decoding process caused by strong inter-reflections. For the remaining uncertain pixels, we apply an iterative algorithm to reduce the inter-reflection within the scene. Thus, more points can be decoded and reconstructed after each iteration. Moreover, the iterative algorithm is carried out in an adaptive fashion for fast convergence.

Style grammars for interactive visualization of architecture.

Interactive visualization of architecture provides a way to quickly visualize existing or novel buildings and structures. Such applications require both fast rendering and an effortless input regimen for creating and changing architecture using high-level editing operations that automatically fill in the necessary details. Procedural modeling and synthesis is a powerful paradigm that yields high data amplification and can be coupled with fast-rendering techniques to quickly generate plausible details of a scene without much or any user interaction. Previously, forward generating procedural methods have been proposed where a procedure is explicitly created to generate particular content. In this paper, we present our work in inverse procedural modeling of buildings and describe how to use an extracted repertoire of building grammars to facilitate the visualization and quick modification of architectural structures and buildings. We demonstrate an interactive application where the user draws simple building blocks and, using our system, can automatically complete the building "in the style of" other buildings using view-dependent texture mapping or nonphotorealistic rendering techniques. Our system supports an arbitrary number of building grammars created from user subdivided building models and captured photographs. Using only edit, copy, and paste metaphors, the entire building styles can be altered and transferred from one building to another in a few operations, enhancing the ability to modify an existing architectural structure or to visualize a novel building in the style of the others.