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The world space defined by a traditional virtual reality application is generally regarded as separate from the real-world space in which users actually exist. In this paper, we present a method that enables such detached spaces to connect in an integrated space. In particular, we show that by using a specially manufactured calibration board and three consumer-grade position tracking devices, a reference coordinate system can easily be set up in the physical space, whose geometric relationship with the virtual reality space is estimated with high numerical accuracy and stability. Then, we demonstrate that, combined with traditional computer vision techniques for marker tracking, the presented technique allows colocated users from virtual, augmented, and mixed realities to cooperate with each other while making effective use of technologies from other realities.

Oxidation of micropollutants (MPs) by ozonation proceeds via the reactions with molecular ozone (O3) and hydroxyl radicals (•OH). To predict MP abatement during ozonation, a model that can accurately predict oxidant exposures (i.e., ∫ 0 t [ O 3 ] d t ⁢ a n d ⁢ ∫ 0 t [ O • H ] d t ) needs to be developed. This study demonstrates machine learning models based on the random forest (RF) algorithm to output oxidant exposures from water quality parameters (input variables) that include pH, alkalinity, dissolved organic carbon concentration, and fluorescence excitation-emission matrix (FEEM) data (to characterize organic matter). To develop the models, 60 different samples of natural waters and wastewater effluents were collected and characterized, and the oxidant exposures in each sample were determined at a specific O3 dose (2.5 mg/L). Four RF models were developed depending on how FEEM data were utilized (i.e., one model free of FEEM data, and three other models that used FEEM data of different resolutions). The regression performance and Akaike information criterion (AIC) were evaluated for each model. The models using high-resolution FEEM data generally exhibited high prediction accuracy with reasonable AIC values, implying that organic matter characteristics quantified by FEEM can be important factors to improve the accuracy of the prediction model. The developed models can be applied to predict the abatement of MPs in drinking water and wastewater ozonation processes and to optimize the O3 dose for the intended removal of target MPs. The machine learning models using higher-resolution FEEM data offer more accurate prediction by better calculating the complex nonlinear relationship between organic characteristics and oxidant exposures.

We propose Neural Crossbreed, a feed-forward neural network that can learn a semantic change of input images in a latent space to create the morphing effect. Because the network learns a semantic change, a sequence of meaningful intermediate images can be generated without requiring the user to specify explicit correspondences. In addition, the semantic change learning makes it possible to perform the morphing between the images that contain objects with significantly different poses or camera views. Furthermore, just as in conventional morphing techniques, our morphing network can handle shape and appearance transitions separately by disentangling the content and the style transfer for rich usability. We prepare a training dataset for morphing using a pre-trained BigGAN, which generates an intermediate image by interpolating two latent vectors at an intended morphing value. This is the first attempt to address image morphing using a pre-trained generative model in order to learn semantic transformation. The experiments show that Neural Crossbreed produces high quality morphed images, overcoming various limitations associated with conventional approaches. In addition, Neural Crossbreed can be further extended for diverse applications such as multi-image morphing, appearance transfer, and video frame interpolation., Comment: 16 pages

We propose a method that generates a virtual camera layout of a 3D animation scene by following the cinematic intention of a reference video. From a reference video, cinematic features such as the start frame, end frame, framing, camera movement, and the visual features of the subjects are extracted automatically. The extracted information is used to generate the virtual camera layout, which resembles the camera layout of the reference video. Our method handles stylized as well as human characters with body proportions different from those of humans. We demonstrate the effectiveness of our approach with various reference videos and 3D animation scenes. The user evaluation results show that the generated layouts are comparable to layouts created by the artist, allowing us to assert that our method can provide effective assistance to both novice and professional users when positioning a virtual camera.

Object detection has been applied in a wide variety of real world scenarios, so detection algorithms must provide confidence in the results to ensure that appropriate decisions can be made based on their results. Accordingly, several studies have investigated the probabilistic confidence of bounding box regression. However, such approaches have been restricted to anchor-based detectors, which use box confidence values as additional screening scores during non-maximum suppression (NMS) procedures. In this paper, we propose a more efficient uncertainty-aware dense detector (UADET) that predicts four-directional localization uncertainties via Gaussian modeling. Furthermore, a simple uncertainty attention module (UAM) that exploits box confidence maps is proposed to improve performance through feature refinement. Experiments using the MS COCO benchmark show that our UADET consistently surpasses baseline FCOS, and that our best model, ResNext-64x4d-101-DCN, obtains a single model, single-scale AP of 48.3% on COCO test-dev, thus achieving the state-of-the-art among various object detectors., Comment: ICIP2021

This paper presents a planar transformer design of a 3-kW 250 kHz SiC-based Auxiliary Power Module (APM) with 3.6 kW/L power density for electric vehicle (xEV) application. The transformer design is optimized based on the trade-off between footprint and magnetic loss using the proposed figure-of-merit (FoM) based optimization. In order to increase the ZVS range of the converter, an additional leakage inductance is implemented using the proposed magnetic integration technique. A comparison between non-integrated and integrated magnetic cores using finite element analysis (FEA) is presented. Results show that the integrated structure can reduce the core loss up to 35% and footprint around 15 % compared to the non-integrated. Experimental results show that all the switches can achieves ZVS under the entire load condition.

In this paper, we present a novel approach for reconstructing 3D geometry from a stream of images captured by a consumer-grade mobile RGB-D sensor. In contrast to previous real-time online approaches that process each incoming image in acquisition order, we show that applying a carefully selected order of (possibly a subset of) frames for pose estimation enables the performance of robust 3D reconstruction while automatically filtering out error-prone images. Our algorithm first organizes the input frames into a weighted graph called the similarity graph. A maximum spanning tree is then found in the graph, and its traversal determines the frames and their processing order. The basic algorithm is then extended by locally repairing the original spanning tree and merging disconnected tree components, if they exist, as much as possible, enhancing the result of 3D reconstruction. The capability of our method to generate a less error-prone stream from an input RGB-D stream may also be effectively combined with more sophisticated state-of-the-art techniques, which further increases their effectiveness in 3D reconstruction.

Practical modeling for assessing the efficiency of a full-scale reverse osmosis (RO) system may be a challenging task. This is because the operating conditions of RO systems can change significantly in actual practice owing to high seasonal variations and different progress of membrane fouling during long-term filtration. Accordingly, it is difficult to reliably model the RO performance if such conditions are excluded. In this study, we model a full-scale installation of a RO membrane system, considering actual operations of the industrial water treatment plant. A numerical model is built to describe spatiotemporal behavior of (water, salt, and foulant) mass transport inside a full-dimension pressure vessel. By performing a global sensitivity analysis, we evaluate the relative importance of key influential factors on model accuracy and specific energy consumption (SEC). The model and its parameters are optimized based on the sensitivity result and validated using best-fitted time-series measurement data of 3875 h. The results demonstrate the practical behaviors of fouling development and separation performance of the primary RO process. A regression tree analysis of SEC for 27 different operational scenarios in simulations may benefit decision making for energy efficient RO. Results reveal the high dependence of SEC on cleaning frequency in the feed temperature range.

Rechargeable seawater battery (SWB) is a unique energy storage system that can directly transform seawater into renewable energy. Placing a desalination compartment between SWB anode and cathode (denoted as seawater battery desalination; SWB‐D) enables seawater desalination while charging SWB. Since seawater desalination is a mature technology, primarily occupied by membrane‐based processes such as reverse osmosis (RO), the energy cost has to be considered for alternative desalination technologies. So far, the feasibility of the SWB‐D system based on the unit cost per desalinated water ($ m−3) has been insufficiently discussed. Therefore, this perspective aims to provide this information and offer future research directions based on the detailed cost analysis. Based on the calculations, the current SWB‐D system is expected to have an equipment cost of ≈1.02 $ m−3 (lower than 0.60–1.20 $ m−3 of RO), when 96% of the energy is recovered and stable performance for 1000 cycles is achieved. The anion exchange membrane (AEM) and separator contributes greatly to the material cost occupying 50% and 41% of the total cost, respectively. Therefore, future studies focusing on creating low cost AEMs and separators will pave the way for the large‐scale application of SWB‐D., Seawater battery desalination (SWB‐D) is a multifunctional system capable of storing energy and removing salt from water simultaneously. This perspective lays out a detailed cost analysis of the system, and provides an insight as to where SWB‐D currently stands in terms of its feasibility and what areas need to be improved to realize large scale applications.

This study examines South Korean print media coverage of two traditional Korean clan villages, Hahoe and Yangdong, both designated World Heritage Site (WHS) in 2010 after nomination to the tentative list in 2001. The study explores the representation of these villages by Korean mass media leading up, and after the process of WHS designation. Findings suggest that the evolution of articulations of heritage and tourism require an event or concern that disrupts the existing interests and needs, and calls upon social agents to consider future implications and opportunities. Some articulations remain for longer periods of time if they continue to serve the needs of the present. The sociocultural significance and implications of the findings are discussed.

In this paper, the classification of animal facial characteristics is examined for the purpose of creating anthropomorphic animal characters, followed by a description of the design process involved in creating a morphing program that can be used to generate various anthropomorphic animal characters. In order to establish an animal archetype database (DB) and an anthropomorphic animal character DB, we systematically analyze the facial characteristics of mammal characters. Subsequently, a technique is proposed with which to express component-based animal faces using a B-Spline curve in the morphing system. This program offers an intuitive user interface with a prototype generated upon the definition of necessary menus that allow system users to select optimally anthropomorphized images from an input source-target image morphing process.

Despite great efforts in recent years to accelerate global illumination computation, the real-time ray tracing of fully dynamic scenes to support photorealistic indirect illumination effects has yet to be achieved in computer graphics. In this paper, we propose an extended ray tracing model that can be readily implemented on a GPU to facilitate the interactive generation of diffuse indirect illumination, the quality of which is comparable to that generated by the traditional, time-consuming photon mapping method and final gathering. Our method employs three types of (multilevel) grids to represent the indirect light in a scene using a form that facilitates the efficient estimation of the reflected radiance caused by diffuse interreflection. This method includes the mathematical tool of spherical harmonics and a rendering scheme that performs the final gathering step with a minimal cost during ray tracing, which guarantees the interactive frame rates. We evaluated our technique using several dynamic scenes with nontrivial complexity, which demonstrated its effectiveness.

We present a simple and effective method for constructing a gallery that consists of weathering effect elements called time-dependent appearance manifolds (TDAMs). Since TDAMs are computed from sample video clips showing dynamic weathering phenomena, they represent very smooth changes in the appearance of weathered pixels over time. Once a gallery with a variety of weathering effects is prepared, users can interactively choose and apply the predefined effects onto the surface of 3D graphic models and then finally assign the most appropriate one. This video-based weathering method can be implemented with very simple algorithms and it supports predictable, intuitive, and natural effects. Our system allows users to produce photorealistic augmented videos that include 3D graphic models weathered by our method. Moreover, users can easily enhance the realism of the augmented videos by manipulating rendering parameters such as the degree of weathering, texturing, lighting, and shadowing through user-friendly graphical user interfaces (GUIs).

The central argument of this book is that there is no one monolithic knowledge that can be generalized into different contexts given that each place or community has its own unique and specific way...

We present the core components to support bidirectional augmented broadcasting services on smart TVs. These components are considered to be very significant for next-generation media services. The key modules used in our proposed system provide users with special functions, allowing them to insert graphic models into common broadcasting contents themselves. Efficiently encoding the tracking information of both the position and orientation of the cameras and the light sources used during an entire video production is the most critical task at the transmitting side. The information is stored in a predefined rendering profile format and is used to render inserted objects photo-realistically and combine them with the original broadcasting contents at the receiving side. We employ cutting-edge techniques developed in the field of computer graphics to display the composed contents seamlessly on smart TVs. This new broadcasting service paradigm will satisfy the needs of high-end users who expect to play the role of content producers.

The light source is an important visual component that empirically affects the color and illumination of graphic objects, and it is necessary to precisely store and appropriately employ the information of all light sources in the real world in order to obtain photo-realistic composition results. The information of real light sources can be accurately stored in HDR environment maps; however, it is impossible to create new environment maps corresponding to dynamic virtual light sources from a single HDR environment map captured under a fixed lighting situation. In this paper, we present a technique to dynamically generate well-matched information for arbitrarily selected virtual light sources using HDR environment maps created under predefined lighting position and orientation. Using the information obtained from light intensity and distribution analysis, our technique automatically generates HDR environment maps for virtual light sources via image interpolation. By applying the interpolated environment maps to an image-based lighting technique, we show that virtual light can create photo-realistically rendered images for graphic models.

A real-time photoacoustic tomography which is capable of imaging the changes in biological features of living subject is presented. A custom developed data acquisition board and linear array transducer is used in this photoacoustic system. A phantom test were carried out to evaluate performance of the system. The developed system showed a satisfactory performance and its usefulness were evaluated. The universal back projection algorithm is used for image reconstruction and the sensitivity is analyzed from the obtained photoacoustic images.

In this paper, we propose an acoustic signal synthesizing algorithm called two-step reconstruction algorithm based on the geometrical information of ROI(region of interest). Even though we apply the same conventional reconstruction algorithm, we can obtain the better image quality of ROI by using the proposed two-step reconstruction algorithm. We comment on the mathematical minor mistakes in applying Residue theorem for the derivation of Green's function in famous paper to which many researchers are still referring. A mathematical k-wave simulation is used for comparing the image quality of ROI with or without two-step reconstruction algorithm. From the simulation results, we prove the effectiveness of proposed acoustic signal synthesizing of two-step reconstruction algorithm.

Because of recent advances in wireless communication technologies, the world of mobile computing is flourishing with a variety of applications. In this study, we present an integrated architecture for a personal digital assistant (PDA)-based mobile medical display system that supports collaborative work between remote users. We aim to develop a system that enables users in different regions to share a working environment for collaborative visualization with the potential for exploring huge medical datasets. Our system consists of three major components: mobile client, gateway, and parallel rendering server. The mobile client serves as a front end and enables users to choose the visualization and control parameters interactively and cooperatively. The gateway handles requests and responses between mobile clients and the rendering server for efficient communication. Through the gateway, it is possible to share working environments between users, allowing them to work together in computer supported cooperative work (CSCW) mode. Finally, the parallel rendering server is responsible for performing heavy visualization tasks. Our experience indicates that some features currently available to our mobile clients for collaborative scientific visualization are limited due to the poor performance of mobile devices and the low bandwidth of wireless connections. However, as mobile devices and wireless network systems are experiencing considerable elevation in their capabilities, we believe that our methodology will be utilized effectively in building quite responsive, useful mobile collaborative medical systems in the very near future.

We present a novel approach that utilizes a simple handheld camera to automatically calibrate multi-projector displays. Most existing studies adopt active structured light patterns to verify the relationship between the camera and the projectors. The utilized camera is typically expensive and requires an elaborate installation process depending on the scalability of its applications. Moreover, the observation of the entire area by the camera is almost impossible for a small space surrounded by walls as there is not enough distance for the camera to capture the entire scene. We tackle these issues by requiring only a portion of the walls to be visible to a handheld camera that is widely used these days. This becomes possible by the introduction of our new structured light pattern scheme based on a perfect submap and a geometric calibration that successfully utilizes the geometric information of multi-planar environments. We demonstrate that immersive display in a small space such as an ordinary room can be effectively created using images captured by a handheld camera.

This paper presents a new scheme for scheduling and control synthesis in high-level circuit design. The scheduling algorithm tries to maximize the performance of a design under resource constraints by maximizing the utilization of resources and minimizing clock slack. It exploits the technique of bit-level chaining (BLC) to target high-speed design. It also exploits noninteger multicycling and chaining, which allows multiple cycle execution of a set of chained operations and even sharing of chained functional units to obtain further performance at the cost of a small increase in the complexity of the control unit. Experimental results on several datapath-intensive designs show significant improvement in throughput over the conventional scheduling algorithms.

This paper presents a new 3D RGB image compression scheme designed for interactive real-time applications. In designing our compression method, we have compromised between two important goals: high compression ratio and fast random access ability, and have tried to minimize the overhead caused during run-time reconstruction. Our compression technique is suitable for applications wherein data are accessed in a somewhat unpredictable fashion, and real-time performance of decompression is necessary. The experimental results on three different kinds of 3D images from medical imaging, image-based rendering, and solid texture mapping suggest that the compression method can be used effectively in developing real-time applications that must handle large volume data, made of color samples taken in three- or higher-dimensional space.

While 2D texture mapping is one of the most effective of the rendering techniques that make 3D objects appear visually interesting, it often suffers from visual artifacts produced when 2D image patterns are wrapped onto the surfaces of objects with arbitrary shapes. On the other hand, 3D texture mapping generates highly natural visual effects in which objects appear carved from lumps of materials rather than laminated with thin sheets as in 2D texture mapping. Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirement. In this paper, we present a new effective method for 3D texture mapping designed for real-time rendering of polygonal models. Our scheme attempts to resolve the potential texture memory problem by compressing 3D textures using a wavelet-based encoding method. The experimental results on various nontrivial 3D textures and polygonal models show that high compression rates are achieved with few visual artifacts in the rendered images and a small impact on rendering time. The simplicity of our compression-based scheme will make it easy to implement practical 3D texture mapping in software/hardware rendering systems including real-time 3D graphics APIs such as OpenGL and Direct3D.

While 2D texture mapping is one of the most powerful rendering techniques that make 3D objects appear visually interesting, it suffers from visual artifacts produced when 2D image patterns are wrapped onto the surface of objects with arbitrary shapes. On the other hand, 3D texture mapping generates highly natural visual effects in which objects appear carved from lumps of materials rather than laminated with thin sheets as in 2D texture mapping. Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirements. In this paper, we present a new effective method for 3D texture mapping designed for real-time rendering of polygonal models. Our scheme attempts to resolve the potential texture memory problem arising from the very large size of 3D images by compressing them using a wavelet-based encoding method. The experimental results on various non-trivial 3D textures and polygonal models show that high compression rates are achieved with few visual artifacts in the rendered image and a small impact on rendering time. The simplicity of our compression-based scheme will make it possible to implement practical 3D texture mapping in software/hardware rendering systems including the real-time 3D graphics APIs like OpenGL and Direct3D.

We have developed an interactive visualization software for an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. Our software utilizes a CAVE system to reconstruct such huge volume datasets as the Visible Human and the Visible Korean Human, produced by NLM and KISTI, respectively. In stead of using the isosurfacing and 3D texture-mapping based volume rendering methods that easily slow down as data sizes increase, our system exploits a new image-based rendering technique to guarantee the effective interactive visualization.

When interactive real-time applications are developed with very large volume data, the use of lossy compression is often inevitable. Lossy compression schemes generally encode data without consideration of the purpose of visualization that is actually performed, which often results in inefficient compression. In this paper, we present a new method for classifying voxels according to their importance in visualization, and assigning appropriate weights to them. The associated weight information can be combined with lossy compression schemes to reduce the visual degradation of reconstructed images, resulting in higher compression rates and visual fidelity. Test results demonstrate that the proposed technique improves both the amount of compression and the quality of visualization significantly.

This paper describes practical issues on designing and implementing industrial built-in self-test circuits for embedded memory test. The proposed test circuits are power conscious, fault locatable, and scan-based-test friendly. These features are notable and useful practically in system-on-a-chip design test because many memories that are repairable and large-sized are commonly embedded in the design. We applied the proposed test circuits to actual RAMs available in industry. Experimental results show that the test circuits are powerful for the RAM test with small penalties of area, delay, and power consumption, compared with no use of the test circuit. Furthermore, the test circuits improve the scan-based testability for the glue logic surrounding the RAMs.

The paper proposes a novel parallel/distributed ray casting scheme for very large volume data that can be effectively used in distributed environments. Our method, based on data compression, attempts to enhance the rendering speedups by quickly reconstructing voxel data from local memory rather than expensively fetching them from remote memory spaces. Our compression based volume rendering scheme minimizes communications between processing elements during rendering computation, hence it is very appropriate for both distributed memory multiprocessors and PC/workstation clusters, where the relatively high communication costs often hinder efficient parallel/distributed processing. We report experimental results on both a Cray T3E and a PC/workstation cluster for the Visible Man dataset.