Satyan R. Coorg

Real-time occlusion culling for models with large occluders

Real-Time Occlusion Culling for Models with Large Occluders SATYAN COORG SETH TELLER Computer Graphics Group MIT Laboratory for Computer Science Efficiently identifying polygons that are visible from a dynamic synthetic viewpoint is an important problem in computer graphics. Typically, visibility determination is performed using the z-buffer algorithm. As this algorithm must examine every triangle in the input scene, z-buffering can consume a significant fraction of graphics processing, especially on architectures that have a low performance or software z-buffer. One way to avoid needlessly processing invisible portions of the scene is to use an occlusion culling algorithm to discard invisible polygons early in the graphics pipeline. In this paper, we exploit the presence of large occluders in urban and architectural models to design a real-time occlusion culling algorithm. Our algorithm has the following features: it is conservative, i.e., it overestimates the set of visible polygons; it exploits spatial coherence by using a hierarchical data structure; and it exploits temporal coherence by reusing visibility information computed for previous viewpoints. The new algorithm significantly accelerates rendering of several complex test models. CR

Calibrated, Registered Images of an Extended Urban Area

We describe a dataset of several thousand calibrated, time-stamped, geo-referenced, high dynamic range color images, acquired under uncontrolled, variable illumination conditions in an outdoor region spanning several hundred meters. The image data is grouped into several regions which have little mutual inter-visibility. For each group, the calibration data is globally consistent on average to roughly five centimeters and 0 1°, or about four pixels of epipolar registration. All image, feature and calibration data is available for interactive inspection and downloading at http://city.lcs.mit.edu/data.Calibrated imagery is of fundamental interest in a variety of applications. We have made this data available in the belief that researchers in computer graphics, computer vision, photogrammetry and digital cartography will find it of value as a test set for their own image registration algorithms, as a calibrated image set for applications such as image-based rendering, metric 3D reconstruction, and appearance recovery, and as input for existing GIS applications.

Temporally coherent conservative visibility

Abstract Efficiently identifying polygons that are visible from a changing synthetic viewpoint is an important problem in computer graphics. Even with hardware support, simple algorithms like depth-buffering cannot achieve interactive frame rates when applied to geometric models with many polygons. However, a visibility algorithm that exploits the occlusion properties of the scene to identify a superset of visible polygons, without touching most invisible polygons, could achieve fast frame rates while viewing such models. In this paper, we present a new approach to the visibility problem. The novel aspects of our algorithm are that it is temporally coherent and conservative ; for all viewpoints the algorithm overestimates the set of visible polygons. As the synthetic viewpoint moves, the algorithm reuses visibility information computed for previous viewpoints. It does so by computing visual events at which visibility changes occur, and efficiently identifying and discarding these events as the viewpoint changes. In essence, the algorithm implicitly constructs and maintains a linearized portion of an aspect graph , a data structure for representing visual events. We demonstrate that the visibility algorithm significantly accelerates rendering of several test models.

Spherical Mosaics with Quaternions and Dense Correlation

We describe an algorithm for generating spherical mosaics from a collection of images acquired from a common optical center. The algorithm takes as input an arbitrary number of partially overlapping images, an adjacency map relating the images, initial estimates of the rotations relating each image to a specified base image, and approximate internal calibration information for the camera. The algorithms output is a rotation relating each image to the base image, and revised estimates of the cameras internal parameters.Our algorithm is novel in the following respects. First, it requires no user input. (Our image capture instrumentation provides both an adjacency map for the mosaic, and an initial rotation estimate for each image.) Second, it optimizes an objective function based on a global correlation of overlapping image regions. Third, our representation of rotations significantly increases the accuracy of the optimization. Finally, our representation and use of adjacency information guarantees globally consistent rotation estimates.The algorithm has proved effective on a collection of nearly four thousand images acquired from more than eighty distinct optical centers. The experimental results demonstrate that the described global optimization strategy is superior to non-global aggregation of pair-wise correlation terms, and that it successfully generates high-quality mosaics despite significant error in initial rotation estimates.

Extracting textured vertical facades from controlled close-range imagery

We are developing a system to extract geodetic, textured CAD models from thousands of initially uncontrolled, close-range ground and aerial images of urban scenes. Here we describe one component of the system, which operates after the imagery has been controlled or geo-referenced. This fully automatic component detects significant vertical facades in the scene, then extrudes them to meet an inferred, triangulated terrain and procedurally generated roof polygons. The algorithm then estimates for each surface a computer graphics texture, or diffuse reflectance map, from the many available observations of that surface. We present the results of the algorithm on a complex dataset: nearly 4,000 high-resolution digital images of a small (200 meter square) office park, acquired from close range under highly varying lighting conditions, amidst significant occlusion due both to multiple inter-occluding structures, and dense foliage. While the results are of less fidelity than that would be achievable by an interactive system, our algorithm is the first to be demonstrated on such a large, real-world dataset.

Calibrated, registered images of an extended urban area

We describe a dataset of several thousand calibrated, geo-referenced, high dynamic range color images, acquired under uncontrolled, variable illumination in an outdoor region spanning hundreds of meters. All image, feature, calibration, and geo-referencing data are available at http://city.lcs.mit.edu/data. Calibrated imagery is of fundamental interest in a wide variety of applications. We have made this data available in the belief that researchers in computer graphics, computer vision, photogrammetry and digital cartography will find it useful in several ways: as a test set for their own algorithms; as a calibrated image set for applications such as image-based rendering, metric 3D reconstruction, and appearance recovery; and as controlled imagery for integration into existing GIS systems and applications. The Web-based interface to the data provides interactive viewing of high-dynamic-range images and mosaics; extracted edge and point features; intrinsic and extrinsic calibration, along with maps of the ground context in which the images were acquired; the spatial adjacency relationships among images; the epipolar geometry relating adjacent images; compass and absolute scale overlays; and quantitative consistency measures for the calibration data.

Temporally coherent conservative visibility (extended abstract)

E ciently identifying polygons that are visible from a changing synthetic viewpoint is an important problem in computer graphics. Even with hardware support, simple algorithms like depth-bu ering cannot achieve interactive frame rates when applied to geometric models with many polygons. However, a visibility algorithm that exploits the occlusion properties of the scene to identify a superset of visible polygons, without touching most invisible polygons, could achieve fast frame rates while viewing such models. In this paper, we present a new approach to the visibility problem. The novel aspects of our algorithm are that it is temporally coherent and conservative; for all viewpoints the algorithm overestimates the set of visible polygons. As the synthetic viewpoint moves, the algorithm reuses visibility information computed for previous viewpoints. It does so by computing visual events at which visibility changes occur, and e ciently identifying and discarding these events as the viewpoint changes. In essence, the algorithm implicitly constructs and maintains a linearized portion of an aspect graph, a data structure for representing visual events.

Partitioning Non-strict Functional Languages for Multi-threaded Code Generation

In this paper, we present a new approach to partitioning, the problem of generating sequential threads for programs written in a non-strict functional language. The goal of partitioning is to generate threads as large as possible, while retaining the non-strict semantics of the program. We define partitioning as a program transformation and design algorithms for basic block partitioning and interprocedural partitioning. The inter-procedural algorithm presented here is more powerful than the ones previously known and is based on abstract interpretation, enabling the algorithm to handle recursion in a straightforward manner. We prove the correctness of these algorithms in a denotational semantic framework.