In this paper, an interactive medical image visualization system to support medical therapy has been introduced, where 3D organ model with the corresponding medical image is visualized interactively for diagnosis and surgical planning. To show effectiveness of the proposed system, 3D liver model generated from CT data has been utilized in consideration of its deformable characteristics by respiration as well as appearance. In addition, a hand gesture interface is applied on the graphical user interface for providing more natural and intuitive interactivity.

This paper introduces a new wide-gamut RGB primary set and a new color-encoding method that are developed for ultrahigh-definition television (UHDTV). The extended gamut RGB-primary set compared with the conventional CRT-centric gamut is proposed in favor of inclusion of real-world surface colors and in consideration of the current and prospective colorimetric characteristics of flat panel displays using which UHDTV programs will likely be reproduced. The new color encoding method is derived to enable luminance and chrominance information to be accurately separated, resulting in orthogonal video signals. The new luma and color-difference signals generated by the newly derived encoding scheme are demonstrated to have insignificant crosstalk. It is also shown that this fact can contribute to improving image quality after subsampling color-difference components and to increasing compression efficiency.

Multiview video sequences with more than 3 color videos and additional supplementary data require huge amount of transmission and storage capacities. This paper proposes novel approaches to transfer such multiview video contents more efficiently by applying a mixed resolution video format and new compression schemes utilizing the characteristics of multiview video contents.

The framework of capturing multiview images has received a great attention from industry as well as academy due to its usability in various applications; 3D scene reconstruction, super-resolution, scene understanding, surveillance etc. This paper presents a multiview capturing system that uses a single camera with multiple mirrors. We place multiple mirrors pointing to the target scene and record an image of those mirrors. From this image of mirrors, we can extract the multiview images of the target scene, images reflected by mirrors. Based on the proposed method, we achieve some success in geometry reconstruction and view synthesis using multiview images, which shows the usability of the proposed work. The main contribution of this work is to introduce a light weight implementation for multiview capturing with a number of useful properties; the automatic synchronization across multiple views, the consistent color/white balance setting across multiple views, the capability of recording a wide range of view and the cost-effective implementation.

Nonlocal means filtering is an edge-preserving denoising method whose filter weights are determined by Gaussian weighted patch similarities. The nonlocal means filter shows superior performance in removing additive Gaussian noise at the expense of high computational complexity. In this paper, we propose an efficient and effective denoising method by introducing a separable implementation of the nonlocal means filter and adopting a bilateral kernel for computing patch similarities. Experimental results demonstrate that the proposed method provides comparable performance to the original nonlocal means, with lower computational complexity.

A three-dimensional (3D) mesh compression algorithm based on novel prediction methods and a mode decision scheme is proposed in this work. After decomposing an input mesh into base and refinement layers, we segment the geometry data of each layer into clusters. To encode vertex positions efficiently, we propose two prediction methods: the dual ring prediction and the minimum mean square error (MMSE) prediction. Also, we develop a mode decision scheme that selects the best prediction mode for each cluster. Simulation results demonstrate that the proposed algorithm provides significantly better compression performance than conventional techniques.

We present a bi-layer inpainting method for synthesizing novel views from a single color image and its corresponding depth map under the exemplar-based inpainting framework. Unlike conventional image inpainting, the decisions of the inpainting direction and the sample regions are important to inpaint disoccluded regions which disclose hidden background regions in the new viewpoint. The proposed algorithm first labels boundaries along the disoccluded regions whether it belongs to the foreground or background objects, and then separates their surrounding regions into the foreground and background regions using the graph cut algorithm. The disoc-cluded regions are then filled from the background boundary with best-match patches taken from the background regions. As demonstrated in the experimental results, the proposed method recovers the disoccluded region with visually plausible quality.

Six-degrees-of-freedom (6-DOF) trackers, which were mainly for professional computer applications, are now in demand by everyday consumer applications. With the requirements of consumer electronics in mind, we designed an optical 6-DOF tracker where a few photo-sensors can track the position and orientation of an LED cluster. The operating principle of the tracker is basically source localization by solving an inverse problem. We implemented a prototype system for a TV viewing environment, verified the feasibility of the operating principle, and evaluated the basic performance of the prototype system in terms of accuracy and speed. We also examined its application possibility to different environments, such as a tabletop computer, a tablet computer, and a mobile spatial interaction environment.

In this work, we propose a progressive compression algorithm using topology-based Karhunen-Loeve transform(KLT). First, we simplify an input mesh to represents an original mesh in several level of details. Then, coordinates of decimated vertices at each level are predicted from the coarser level mesh, and the prediction residuals are transmitted to a decoder. To provide high coding efficiency, we apply the topology-based KLT, which compacts the energy into a few coefficients, to the prediction residuals. Moreover, we develop a bit plane coder, which uses a context-adaptive arithmetic coder, for the entropy coding. Experiments on various 3D meshes show that the proposed algorithm provides enhanced compression performance.

Time-of-Flight depth cameras provide a direct way to acquire range images, using the phase delay of the incoming reflected signal with respect to the emitted signal. These cameras, however, have a challenging problem called range folding, which occurs due to the modular error in phase delay—ranges are modulo the maximum range. To our best knowledge, we exploit the first approach to estimate the number of mods at each pixel from only a single range image. The estimation is recasted into an optimization problem in the Markov random field framework, where the number of mods is considered as a label. The actual range is then recovered using the optimal number of mods at each pixel, so-named range unfolding. As demonstrated in the experiments with various range images of real scenes, the proposed method accurately determines the number of mods. In result, the maximum range is practically extended at least twice of that specified by the modulation frequency.

This paper presents a novel algorithm for realistic 3D face modeling from a single pair of color and time-of-flight (TOF) depth images using a generic, deformable model. Most previous approaches have attempted to emphasize either facial feature or global shape consistency, resulting in either visually plausible or geometrically accurate models. In this paper, we introduce feature-preserving surface registration to achieve both reality and accuracy. The proposed algorithm takes advantages of both facial features from the color image and geometric information from the depth image in an iterative closest point (ICP) framework, where the non-rigid registration is achieved by iteratively minimizing the energy function consisting of feature distance term, surface distance term, and linear elasticity term. As demonstrated in the experimental results, the proposed algorithm builds the personalized 3D face model within a few seconds with high visual quality.

In this paper, we described geometric prediction structure for multi-view video coding. By exploiting the geometric relations between each camera pose, we can make prediction pair which maximizes the spatial correlation of each view. To analyze the relationship of each camera pose, we defined the mathematical mean view and view distance in 3D space. We proposed an algorithm for establishing the geometric prediction structure based on view center and view distance. Using this prediction structure, inter-view prediction is performed to camera pair of maximum spatial correlation. In our prediction structure, we also considered the view scalability. Experiments are done using JMVC software on MPEG-FTV test sequences. Overall performance is measured in the PSNR and subjective image quality measure such as PSPNR.

In this paper, we present a new video coding scheme to improve coding efficiency. For this purpose, we develop a loop filter that restores the compressed pictures in accordance with the image local characteristic. More specifically, a picture is segmented in such a way that the rate distortion cost is minimized and each pixel of the picture is restored using Wiener filter specific to the region. The restored picture is used for the motion-compensated prediction of future pictures and this can improve coding efficiency. In particular, we propose segmentation mode to reflect the local attributes of a picture. Finally, video coding that performs the new approach is implemented and results in 12.7% BD-bitrate reduction on average in Baseline Profile when compared to H.264/AVC.

This paper presents a novel approach to face modeling for realistic synthesis, powered by a probabilistic face diffuse model and a generic face specular map. We first construct a probabilistic face diffuse model for estimating the albedo and the normals of a face from an unknown input image. Then, we introduce a generic face specular map for estimating the specularity of the face. Using the estimated albedo, normal and specular information, we can synthesize the face under arbitrary lighting and viewing directions realistically. Unlike many existing face modeling techniques, our approach can retain both the diffuse and specular properties of the face without involving an elaborating 3D matching procedure. Thanks to the compact representation and the effective inference scheme, our technique can be applied to many practical applications, such as face normalization, avatar creation and de-identification.

The recent online networked virtual worlds such as SecondLife, World of Warcraft and Lineage have been increasingly popular. A life-scale virtual world presentation and the intuitive interaction between the users and the virtual worlds would provide more natural and immersive experience for users. The emergence of novel interaction technologies such as sensing the facial expression and the motion of the users and the real world environments could be used to provide a strong connection between them. For the wide acceptance and use of the virtual world, a various type of novel interaction devices should have a unified interaction formats between the real world and the virtual world and interoperability among virtual worlds. Thus, MPEG-V Media Context and Control (ISO/IEC 23005) standardizes such connecting information. The paper provides an overview and its usage example of MPEG-V from the real world to the virtual world (R2V) on interfaces for controlling avatars and virtual objects in the virtual world by the real world devices. In particular, we investigate how the MPEG-V framework can be applied for the facial animation of an avatar in various types of virtual worlds.

This paper presents a bidirectional motion estimation (ME) method based on tracking feature trajectories and compensating for occlusion to enhance the temporal resolution of an input video sequence. First, we extract features and estimate their trajectories in the forward direction. We continue to track features only if the reliability of their trajectory is sufficiently high. Accordingly, if a feature can be continuously tracked through multiple frames, the proposed method assumes that its trajectory is a true motion vector (MV). Then, these forward feature trajectories are used as reference motion directions for backward block-based ME. If a block does not include any feature trajectories, we use the MVs of neighboring blocks as candidate MVs to propagate the predetermined true MV and preserve the spatial correlation of MVs. Further, the proposed method can detect occlusion regions, where a continuously tracked feature does not have a corresponding point in the current frame. In the detected occlusion region, the intermediate frame is generated from either the previous frame or the current frame. Outside the occlusion region, we generate the intermediate frames by taking into consideration the neighboring MVs to reduce blocking artifacts. Experimental results show that the proposed temporal frame interpolation (TFI) method can improve visual quality over conventional TFI methods, both objectively and subjectively.

X-ray projection is not effective for representing complex overlapping objects. This paper presents a novel computational framework to decompose X-ray projections into multiple images with non-overlapping objects that are differentiated by their own material compositions. Based on energy-dependent X-ray attenuation characteristics for each material, multiple energy X-ray images are analyzed to obtain material-selective images, which correspond to projections of basis materials that constitute objects. We show that material-selective images can be considered as linear mixtures of independent components that are associated with object-selective images. As a result, multiple objects can be decomposed by independent component analysis (ICA) of material-selective images or ICA of multiple monochromatic energy X-ray images. To demonstrate the concept of the proposed method, we apply it to simulated images based on a 3-D human model.

Images captured from digital camera suffer noise due to high sensor gain under dark conditions. Furthermore, camera-shake is unavoidable when exposure time is long enough to have desirable SNR. This paper presents an image capturing method that enhances image quality in low-light environments by fusing visible-band (400 ~ 700 nm) image and wide-band (400 ~ 1000 nm) image. Wide-band image has lower noise, richer detail and a monotonic color. Visible-band image has higher noise, poorer detail and a trichromatic color. We describe how the advantages of these images are exploited to create new image that is of higher quality. Experiments demonstrate that the proposed method significantly improves quality of images under low illumination conditions.

Today's display devices are incapable of reproducing the full color range that humans can perceive; hence, color gamut expansion technology has become an active area of research. Among other things, the multi-primary display (MPD) device has received much attention lately because it provides simple and effective mechanisms for widening the color gamut. However, MPD has problems related to over-determined systems and metamerism. This paper seeks to provide solutions to these problems by proposing a cusp mapping method to address gamut mapping issues and LUT implementation of dimension reduction of over-determined systems to address primary decomposition issues. The proposed methods were tested on a 5-primary DLP/sup TM/ projection television. The experimental results address metamerism issues and show increasing as much as 20% at the color-reproducing region that the most common 3-primary DLP/sup TM/ projection television can not reproduce.