Visual Computing for Industry, Biomedicine, and Art最新文献

In this paper, we propose an efficient computational method for converting local coordinates to world coordinates using specially structured coordinate data. The problem in question is the computation of world coordinates of an object throughout a motion, assuming that we only know the changing coordinates of some fixed surrounding reference points in the local coordinate system of the object. The proposed method is based on barycentric coordinates; by taking the aforementioned static positions as the vertices of a polyhedron, we can specify the coordinates of the object in each step with the help of barycentric coordinates. This approach can significantly help us to achieve more accurate results than by using other possible methods. In the paper, we describe the problem and barycentric coordinate-based solution in detail. We then compare the barycentric method with a technique based on transformation matrices, which we also tested for solving our problem. We also present various diagrams that demonstrate the efficiency of our proposed approach in terms of precision and performance.

The evolution of the Internet has enabled us to enjoy the music created in various countries. But still, it is often difficult to understand the lyrics written in foreign languages. Professional translators have published many international songs with lyrics that fit the melody so that the ordinary people can enjoy the lyrics of such international songs. This paper discusses lyrics transcreation into the Japanese language. Also, the paper presents an interactive visual lyrics transcreation system and describes the details of its implementation. This system allows users to select temporary lyrics from a set of tentative translations and then freely modify the lyrics with a real-time visualization mechanism. We also propose a lyrics translation algorithm that solves an essential problem of lyrics translation into Japanese. In this study, we interviewed two experts regarding problems with lyrics translation and received reviews of our presented system. We also conducted preliminary experiments with 19 participants to determine the best combination of user interface components for our system. We performed additional user experiments inviting 12 participants to compare lyrics transcreation using the presented system to manual lyrics transcreation. Lyrics transcreation by the presented system brought better results against those of manual transcreation.

Due to the beam-hardening effect of the broad energy spectrum of the X-ray source in computed tomography, the reconstructed images usually suffer from severe artifacts when metallic objects are being imaged. Metal artifact correction methods are usually sophisticated and not practical, especially in some non-medical applications, in which the linear attenuation coefficients are unknown. This paper suggests a simple and effective algorithm to estimate the unreliable measurements. The proposed algorithm is an iterative algorithm, in which the iteration is performed in the projection domain, while the objective function is set up in the image domain. The final image is reconstructed with the conventional filtered backprojection algorithm. The feasibility of the proposed method is verified with airport bags that contain some unknown metals.

In the construction area, visuals such as drawings, photos, videos, and 3D models, play a significant role in the design, build and maintenance of a facility, bringing efficiency to generate, transfer, and store information. Advanced visual computing techniques facilitate the understanding of design contents, work plans, and other types of information shared in the construction industry. Automatic visual data collection and analysis provide many possibilities to the construction industry and a large number of works have investigated how visual computing can improve construction management processes and other problems in the construction area. However, a comprehensive literature review is needed. This study uses bibliometric approaches to review the works published to date, and analyses the development of knowledge, significant research results, and trends. The purpose of this study is to help newcomers to this research field understand knowledge structure and formulate research directions, thereby enhancing knowledge development. From this study, it can be concluded that computer vision is a key axis of improvement. Moreover, building information modeling, laser scanning, and other visualization-related techniques are also important in advancing the construction area.

We present a mixed reality-based assistive system for shading paper sketches. Given a paper sketch made by an artist, our interface helps inexperienced users to shade it appropriately. Initially, using a simple Delaunay-triangulation based inflation algorithm, an approximate depth map is computed. The system then highlights areas (to assist shading) based on a rendering of the 2.5-dimensional inflated model of the input contour. With the help of a mixed reality system, we project the highlighted areas back to aid users. The hints given by the system are used for shading and are smudged appropriately to apply an artistic shading to the sketch. The user is given flexibility at various levels to simulate conditions such as height and light position. Experiments show that the proposed system aids novice users in creating sketches with impressive shading.

A linear denoising filter is usually of lowpass type, and the main parameter in a lowpass filter is the cutoff frequency. The lowpass filters are normally shift invariant and can be implemented as convolution in the spatial domain or as multiplication in the Fourier domain. This paper presents a linear filter that is not characterized by its cutoff frequency but is characterized by the noise model. An example of such a linear filter is presented for low-dose X-ray computed tomography (CT).

Recently, so-called tree-based phylogenetic networks have attracted considerable attention. These networks can be constructed from a phylogenetic tree, called the base tree, by adding additional edges. The primary aim of this study is to provide sufficient criteria for tree-basedness by reducing phylogenetic networks to related graph structures. Even though it is generally known that determining whether a network is tree-based is an NP-complete problem, one of these criteria, namely edge-basedness, can be verified in linear time. Surprisingly, the class of edge-based networks is closely related to a well-known family of graphs, namely, the class of generalized series-parallel graphs, and we explore this relationship in full detail. Additionally, we introduce further classes of tree-based networks and analyze their relationships.

Irregular fine protrusions formed on the surface of a mechanical part through biomimetic technology can enhance the part's properties, including tribology, self-cleaning, and light absorption. However, underlying principles for the formation of fine protrusions according to the requirements of their shapes, sizes, and material distributions have not been studied sufficiently. This paper presents the software development for modeling irregular fine protrusions, which is essential for the simulation, experimentation, and analysis of fine protrusions formed by sputter etching.

Image reconstruction for list-mode time-of-flight (TOF) positron emission tomography (PET) can be achieved by analytic algorithms. The backprojection filtering (BPF) algorithm is an efficient algorithm for this task. The conventional noise control method for analytic image reconstruction is the use of a stationary lowpass filter, which does not model the Poisson noise properly. This study proposes a nonstationary filter for Poisson noise control. The filter is implemented in the spatial domain in a form similar to convolution.

The state-of-the-art approaches for image reconstruction using under-sampled k-space data are compressed sensing based. They are iterative algorithms that optimize objective functions with spatial and/or temporal constraints. This paper proposes a non-iterative algorithm to estimate the un-measured data and then to reconstruct the image with the efficient filtered backprojection algorithm. The feasibility of the proposed method is demonstrated with a patient magnetic resonance imaging study. The proposed method is also compared with the state-of-the-art iterative compressed-sensing image reconstruction method using the total-variation optimization norm.