Coverage-Based Opacity Estimation for Interactive Depth of Field in Molecular Visualization

Coverage-Based Opacity Estimation for Interactive Depth of Field in Molecular Visualization

Coverage-Based Opacity Estimation for Interactive Depth of Field in Molecular Visualization Sathish Kottravel∗ Martin Falk∗ Erik Sunden´ ∗ Timo Ropinski† ∗ Interactive Visualization Group, Linkoping¨ University, Sweden † Visual Computing Research Group, Ulm University, Germany Figure 1: Thermus thermophilus 70S ribosome (PDB ID: 2WDK) rendered with no Depth of Field effect (left) and using our approach focusing on near structures (center) and far away structures (right). ABSTRACT 1 INTRODUCTION To better understand the underlying mechanisms of life, it is es- In this paper, we introduce coverage-based opacity estimation to sential to investigate the structure of molecules. Considering the achieve Depth of Field (DoF) effects when visualizing molec- structure-follows-function paradigm, the understanding of a pro- ular dynamics (MD) data. The proposed algorithm is a novel tein’s structure for instance can give essential hints about its role object-based approach which eliminates many of the shortcom- in metabolic pathways. Furthermore, when dealing with more than ings of state-of-the-art image-based DoF algorithms. Based on one molecule, their structure can give us clues about potential bind- observations derived from a physically-correct reference renderer, ing sites for molecule interactions. Besides those cases requir- coverage-based opacity estimation exploits semi-transparency to ing depictions of individual molecules, visualizing the multitude simulate the blur inherent to DoF effects. It achieves high qual- of molecules within the crowded environment of the cell also calls ity DoF effects, by augmenting each atom with a semi-transparent for improved spatial comprehension. While modern life science shell, which has a radius proportional to the distance from the fo- technologies result in detailed molecular models as well as sim- cal plane of the camera. Thus, each shell represents an additional ulations containing hundreds of thousands of instances, enabling coverage area whose opacity varies radially, based on our observa- an improved spatial comprehension of these models can be chal- tions derived from the results of multi-sampling DoF algorithms. lenging. As a consequence, modern visualization algorithms often By using the proposed technique, it becomes possible to generate struggle with the complexity of the data, which renders the applica- high quality visual results, comparable to those achieved through tion of advanced techniques tailored for improved spatial compre- ground-truth multi-sampling algorithms. At the same time, we ob- hension difficult. tain a significant speedup which is essential for visualizing MD data In recent years, several visualization algorithms have been de- as it enables interactive rendering. In this paper, we derive the un- veloped for improving the spatial comprehension of complex data derlying theory, introduce coverage-based opacity estimation and sets, as they are acquired through imaging or result from simula- demonstrate how it can be applied to real world MD data in or- tions. These algorithms can be roughly classified into two groups: der to achieve DoF effects. We further analyze the achieved results physically-inspired and illustrative algorithms. While physically- with respect to performance as well as quality and show that they inspired algorithms are often based on the fundamental physical are comparable to images generated with modern distributed ray principles underlying light transport, illustrative algorithms borrow tracing engines. from traditional hand drawn depictions. In this paper, we tackle the problems related to spatial comprehension of large molecular data Index Terms: I.3.7 [Computer Graphics]: Three-Dimensional sets, by proposing a physically-inspired DoF algorithm which has Graphics and Realism—Color, shading, shadowing, and texture specifically been developed for molecular data sets as illustrated in Figure 1. DoF techniques emerged from computer graphics, where they are often used to generate more realistic renderings. By de- ∗email: [email protected] picting objects sharp in the focus area and increasing their blur de- †e-mail: [email protected] pending on the distance to the focus area, these algorithms mimic the behavior of real world camera lenses. As DoF is so widely used in photography, it has also received attention within scientific visualization for Focus+Context (F&C) [8, 23, 22] purposes. F&C is a general concept for directing the per pixel on the surface of a lens [2]. Thus, they could generate ac- curate DoF effects by simulating light transport between the cam- era and the scene whereby the pixel contributions are calculated across multiple samples instead of one ray originating from a sin- gle point. As multiple rays result in varying visibility for each pixel, this method correctly considers partial occlusion between objects. In particular, this method inherently handles some of the common artifacts that can occur during DoF computation such as intensity leakages and depth discontinuities which occur in modern image- based methods [3]. However, in order to obtain accurate results (a) (b) with multi-sampling, a high number of samples is required, which renders this method computationally too expensive for real-time ap- Figure 2: Comparison of our method with an image-based DoF ap- plications. To tackle these performance problems, an alternative proach. (a) our coverage-based DoF. (b) image-based DoF by post- approach was formulated by Haeberli and Akeley to approximate processing depth and color buffer. Even for such relatively small DoF effects by using the z-buffer together with an accumulation molecular structures the image-based approach suffer from severe buffer [7]. Instead of casting multiple rays, a scene is rendered in artifacts that are not visible in our object-based approach. several passes from different positions on the lens and the accu- mulated result is blended. While a high number of passes leads to accurate DoF results, this method can generate convincing DoF viewers attention onto certain parts of picture, and in scientific vi- effects at interactive frame rates by using fewer passes. sualization its usage is motivated by exploration of large complex In subsequent years, several methods were developed to approx- structures. Furthermore, as large complex structures normally con- imate DoF computations with the goal to obtain real-time render- tain small and large varying spatial locations, an adaptive F&C ing. This new stream of DoF rendering algorithms is referred to based on depth such as DoF becomes essential, as the focus needs as image-based, post-filtering methods. This group of techniques to be controlled to correctly visualize the data in the desired context. exploits blurring to obtain DoF effects, whereby the blur can be More recently, DoF techniques have also been utilized in visualiza- achieved by using a single or multiple layers. In single layer ap- tion where it has been shown that they have a positive effect on the proaches a scattering technique can be used in which the pixel val- depth perception of complex scenes [4]. ues are scattered to neighboring pixels within the CoC in image While volumetric DoF techniques can be directly integrated into space. Then the scattered pixels are accumulated and blended after the volume rendering process [20], image-based post-processing depth sorting. Shinya used random multi-sampling to achieve jitter- techniques are often used for surface-based models. This is due to ing that circumvents the partial occlusion problem which demands the fact that the physically-correct multi-sampling approach, which additional computational costs [21]. As an alternative to the scat- directly takes into account the lens geometry, often forbids inter- tering approach, blurring can also be achieved by gathering pixel active frame rates due to the increased sampling complexity, while values from neighboring pixels within the CoC. As gathering is re- the image-based post-processing effects can be applied in real-time. alized by using filtering techniques, visual artifacts like intensity Unfortunately, they introduce artifacts, such as incorrect DoF ef- leakages are almost unavoidable. Both, scattering and gathering as fects along the silhouettes of occluding objects (see Figure 2). As single layer, post-filtering methods, do not address blurring discon- inter-atom occlusions are predominant in molecular data sets, it is tinuities. With the aid of multi-layer approaches it is possible to mandatory to resolve this issue while still allowing for interactive address partial occlusion artifacts effectively by taking the object data exploration. To avoid this artifacts and still enable interactive space into account. Therefore, the scene is decomposed into sev- frame rates, we propose a novel object-based algorithm for realiz- eral distinct layers that do not overlap in depth. Each of these layers ing DoF effects for MD data sets. is then blurred before the layers are composited in back-to-front or- To address the shortcomings related to image-based DoF effects, der. Based on this approach many methods have been proposed to we analyzed the nature of DoF effects as generated by a physically- achieve DoF effects, e.g., [14, 18]. Instead, our method is related to correct multi-sampling renderer, and derived an object-based algo- the scattering paradigm. However, we avoid explicit scattering of rithm from these observations. The core idea of the proposed algo- pixels

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