Improved Alpha Testing Using Hashed Sampling Wyman, Chris; McGuire, Morgan
IEEE transactions on visualization and computer graphics,
02/2019, Letnik:
25, Številka:
2
Journal Article
Recenzirano
We further describe and analyze the idea of hashed alpha testing from Wyman and McGuire <xref ref-type="bibr" rid="ref1">1 , which builds on stochastic alpha testing and simplifies stochastic ...transparency. Typically, alpha testing provides a simple mechanism to mask out complex silhouettes using simple proxy geometry with applied alpha textures. While widely used, alpha testing has a long-standing problem: geometry can disappear entirely as alpha mapped polygons recede with distance. As foveated rendering for virtual reality spreads, this problem worsens as peripheral minification and prefiltering introduce this problem on nearby objects. We first introduce the notion of stochastic alpha testing , which replaces a fixed alpha threshold of <inline-formula><tex-math notation="LaTeX">\alpha _\tau =0.5</tex-math> <inline-graphic xlink:href="wyman-ieq1-2739149.gif"/> </inline-formula> with a randomly chosen <inline-formula><tex-math notation="LaTeX">\alpha _\tau \in 0..1)</tex-math> <inline-graphic xlink:href="wyman-ieq2-2739149.gif"/> </inline-formula>. This entirely avoids the problem of disappearing alpha-tested geometry, but introduces temporal noise. Hashed alpha testing uses a hash function to choose <inline-formula><tex-math notation="LaTeX">\alpha _\tau</tex-math> <inline-graphic xlink:href="wyman-ieq3-2739149.gif"/> </inline-formula> procedurally. With a good hash function and inputs, hashed alpha testing maintains distant geometry without introducing more temporal flicker than traditional alpha testing. We also describe how hashed alpha interacts with temporal antialiasing and applies to alpha-to-coverage and screen-door transparency. Because hashed alpha testing addresses alpha test aliasing by introducing stable sampling, it has implications in other domains where increased sample stability is desirable. We show how our hashed sampling might apply to other stochastic effects.
The cartogram, or value-by-area map, is a popular technique for cartographically representing social data. Such maps visually equalize a basemap before mapping a social variable by adjusting the size ...of each enumeration unit by a second, related variable. However, to scale the basemap units according to an equalizing variable, cartograms must distort the shape and/or topology of the original geography. Such compromises reduce the effectiveness of the visualisation for elemental and general map-reading tasks. Here we describe a new kind of representation, termed a value-by-alpha map, which visually equalizes the basemap by adjusting the alpha channel, rather than the size, of each enumeration unit. Although not without its own limitations, the value-by-alpha map is able to circumvent the compromise inherent to the cartogram form, perfectly equalizing the basemap while preserving both shape and topology.
This study presents a technique to automatically extract the aircraft from video sequences. The technique incorporates object tracking algorithm to separate the region of interest (ROI), i.e. ...movement of aircraft, from video sequence, to reduce the computational complexity. Trimaps are generated automatically for given ROI using non-rigid image registration to obtain the prior information of the object and alpha mattes are estimated for each frame using KNN matting algorithm. However, the alpha matte of static region is estimated only once, that is combined with the alpha matte of moving region to generate final alpha matte. Simulations performed on different videos show that the proposed technique not only reduces the computational complexity, but also gives competitive results by generating high quality alpha maps.
In this paper, we propose a framework for extending existing matting methods to actualize more reliable alpha estimation. The key idea of the framework is integration of multiple alpha maps based on ...their reliabilities. In the proposed framework, the given input image is converted into multiple grayscale images having various luminance appearances. Then, alpha maps are generated corresponding to these grayscale images by utilizing an existing matting method. At the same time reliability maps (single channel images visualizing the reliabilities of the estimated alpha values) are generated. Finally, by combining alpha maps having the highest reliabilities in each local region, one reliable alpha map is generated. The experimental results have shown that reliable alpha estimation can be actualized by the proposed framework.
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