One of the major challenges in developing techniques for realistic and high performance visualization of outdoor environments is rendering of vegetation. The greatest problem is that convincing modeling of trees, bushes and undergrowth requires very large numbers of polygons that exceed the limits posed by rendering hardware today (and in the near future). A number of methods have been proposed in the past to address the issue, most of which are variants of multi-resolution modeling and level-ofdetail algorithms. This paper reviews some of the landmark techniques used in real-time PC applications (mostly games and flight-simulators), and presents a solution that takes advantage of the programmable rendering pipelines available on most of the recent video cards. The algorithm uses view dependent 2.5 dimensional impostors to visualize trees in convincing quality for most levels of detail. Numeric results are presented to illustrate rendering efficiency, and specific, implementation related issues are also discussed.

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This paper proposes a robust algorithm to detect colon polyps and cancerous lesions in virtual colonoscopy and present them to the user by automatically guiding the virtual camera. The detection algorithm uses Gaussian filters to construct the Hessian matrix, which represents the second order derivatives of a vector variate scalar valued function. Based on the sign and scale of the eigenvalues of the Hessian matrix, blob like lesions can be selected on a given scale. In the visualization stage the camera is moved along the colon centerline with its speed and viewing direction adopted to the results of detection. The camera path and the viewing direction are described by Kochanek-Bartels splines. The velocity along the path is also governed by a C 2 continuous function. The resulting fly through is smooth and physically plausible, and it is guaranteed that the user can see all regions of interest and spends sufficient time looking at each of them.