"高效剔除场景元素：可见序列集计算与应用（HELSINKI UT演示）"

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sibility information using Potentially Visible Set (PVS) techniques. In this seminar on computer graphics at Helsinki University of Technology, the focus was on understanding and implementing PVS for real-time 3D graphics. PVS is a method used to determine the visibility of objects in a scene from a given viewpoint. By precomputing a set of potentially visible objects, the rendering process can be optimized by only drawing the objects that are actually visible to the camera. This can significantly reduce the computational cost of rendering complex scenes with many objects. The calculation of the Potentially Visible Set involves determining which objects in the scene are potentially visible from a given viewpoint. This is typically done by performing visibility tests between the objects and the viewpoint, and storing the results in a data structure for efficient access during the rendering process. One of the key challenges in implementing PVS is determining the trade-off between the accuracy of the visibility information and the computational cost of calculating and storing the PVS data. The goal is to find a balance that provides significant rendering performance improvements without introducing noticeable visual artifacts. In the seminar, Mikko Laakso presented his research on PVS and discussed various algorithms for calculating the Potentially Visible Set. He demonstrated how PVS can be used in real-time 3D graphics applications to achieve smooth and efficient rendering of complex scenes. Overall, the seminar provided valuable insights into the importance and practical applications of PVS in the field of computer graphics. By understanding and implementing PVS techniques, graphics developers can optimize rendering performance and create more immersive and realistic 3D experiences.

2 PVS TECHNIQUES

Calculating the potentially visible set is not always easy. Limited resolution and the

question of sample point count and placement are just few of the problems. Over the

years many different techniques have been developed to perform this task. These

solutions can be loosely categorized (Nirenstein et al, 2002) into those applied either

run-time of during a pre-process. With a few exceptions, the former determine the

visibility from a single point, while the latter establish the subset of geometry visible

from any point within a region. From-region visibility partitions the view-point space

into regions of cells, rather than attempting to preprocess the infinite number of possible

camera positions. The principal advantage of these techniques is that their considerable

computation cost can be shifted to a pre-process, consequently removing significant run-

time visibility computation. The results may then be saved to disk for future use. The

disadvantage is that, as a pre-process, only static scenes can be fully treated. From-point

visibility algorithms are less costly computationally than from-region approaches,

allowing them to be applied on a per-frame basis at run-time. They are also better suited

to unpredictably dynamic environments, where the share or position of objects may

change between frames.

Occlusion culling algorithms may be further categorized according to their accuracy in

differentiating between visible and hidden polygons. Nirenstein et al. (2002) compare

algorithms by image quality (correct or containing errors) and run-time performance

(optimal or sub-optimal) and discriminate between conservative, aggressive,

approximate and exact visibility algorithms.

•

Conservative techniques consistently overestimate visibility and incur a false

visibility error: hidden polygons are considered visible. This naturally gives correct

images but results in sub-optimal run-time performance because some polygons are

unnecessarily submitted to rendering pipeline. In decent conservative algorithms the

conservativity should be no more than 30%.

•

Aggressive methods always underestimate the set of visible geometry and exhibit

false invisibility, where visible polygons are erroneously excluded. Aggressive

visibility causes image error but can be useful if the perceptual impact of the error is

acceptably small or the algorithm handles scenes that cannot be solved effectively

with conservative alternative due to excessive overestimation. However, in practise

even rather small image errors are usually quite noticeable and thus unacceptable.

•

Approximate visibility techniques give both false visibility and false invisibility

errors. They are thus useful usually only when the pre-processing efficiency is the

overriding concern.

•

Exact visibility solutions provide both accurate images and optimal rendering

performance. An exact visibility query will produce no more or less than the union

of the polygons visible from all viewpoints within the region.

There exists several surveys of different computer graphics occlusion culling techniques

and algorithms. An interested reader may look for example Zhang (1998), Saona-

Vasquez et al. (1999), Durand (1999), Cohen-Or et al. (2001) and Bittner (2002). The

following chapters of this paper present some of the most interesting solutions.

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error to accept an incorrect (and potentially broken) dependency resolution.

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The request was rejected because the URL contained a potentially malicious String ";

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