Image resizing is a key technique for displaying images on different devices, and has attracted much attention in the past few years. This paper reviews the image resizing methods proposed in recent years, gives a detailed comparison on their performance, and reveals the main challenges raised in several important issues such as preserving an important region, minimizing distortions, and improving efficiency. Furthermore, this paper discusses the research trends and points out the possible hotspots in this field. We believe this survey can give some guidance for researchers from relevant research areas, offering them an overall and novel view.

Anti-aliasing is a well-established technique in computer graphics that reduces the blocky or stair-wise appearance of pixels. This paper provides a comprehensive overview of the anti-aliasing techniques used in computer graphics, which can be classified into two categories: post-filtering based anti-aliasing and pre-filtering based anti-aliasing. We discuss post-filtering based anti-aliasing algorithms through classifying them into hardware anti-aliasing techniques and post-process techniques for deferred rendering. Comparisons are made among different methods to illustrate the strengths and weaknesses of every category. We also review the utilization of anti-aliasing techniques from the first category in different graphic processing units, i.e., different NVIDIA and AMD series. This review provides a guide that should allow researchers to position their work in this important research area, and new research problems are identified.

Random needle embroidery (RNE) is a graceful art enrolled in the world intangible cultural heritage. In this paper, we study the stitch layout problem and propose a controllable stitch layout strategy for RNE. Using our method, a user can easily change the layout styles by adjusting several high-level layout parameters. This approach has three main features: firstly, a stitch layout rule containing low-level stitch attributes and high-level layout parameters is designed; secondly, a stitch neighborhood graph is built for each region to model the spatial relationship among stitches; thirdly, different stitch attributes (orientations, lengths, and colors) are controlled using different reaction-diffusion processes based on a stitch neighborhood graph. Moreover, our method supports the user in changing the stitch orientation layout by drawing guide curves interactively. The experimental results show its capability for reflecting various stitch layout styles and flexibility for user interaction.

In the area of 3D digital engineering and 3D digital geometry processing, shape simplification is an important task to reduce their requirement of large memory and high time complexity. By incorporating the content-aware visual salience measure of a polygonal mesh into simplification operation, a novel feature-aware shape simplification approach is presented in this paper. Owing to the robust extraction of relief heights on 3D highly detailed meshes, our visual salience measure is defined by a center-surround operator on Gaussian-weighted relief heights in a scale-dependent manner. Guided by our visual salience map, the feature-aware shape simplification algorithm can be performed by weighting the high-dimensional feature space quadric error metric of vertex pair contractions with the weight map derived from our visual salience map. The weighted quadric error metric is calculated in a six-dimensional feature space by combining the position and normal information of mesh vertices. Experimental results demonstrate that our visual salience guided shape simplification scheme can adaptively and effectively re-sample the underlying models in a feature-aware manner, which can account for the visually salient features of the complex shapes and thus yield better visual fidelity.

We propose an angle-based mesh representation, which is invariant under translation, rotation, and uniform scaling, to encode the geometric details of a triangular mesh. Angle-based mesh representation consists of angle quantities defined on the mesh, from which the mesh can be reconstructed uniquely up to translation, rotation, and uniform scaling. The reconstruction process requires solving three sparse linear systems: the first system encodes the length of edges between vertices on the mesh, the second system encodes the relationship of local frames between two adjacent vertices on the mesh, and the third system defines the position of the vertices via the edge length and the local frames. From this angle-based mesh representation, we propose a quasi-angle-preserving mesh deformation system with the least-squares approach via handle translation, rotation, and uniform scaling. Several detail-preserving mesh editing examples are presented to demonstrate the effectiveness of the proposed method.

A novel representation of a triangular mesh surface using a set of scale-invariant measures is proposed. The measures consist of angles of the triangles (triangle angles) and dihedral angles along the edges (edge angles) which are scale and rigidity independent. The vertex coordinates for a mesh give its scale-invariant measures, unique up to scale, rotation, and translation. Based on the representation of mesh using scale-invariant measures, a two-step iterative deformation algorithm is proposed, which can arbitrarily edit the mesh through simple handles interaction. The algorithm can explicitly preserve the local geometric details as much as possible in different scales even under severe editing operations including rotation, scaling, and shearing. The efficiency and robustness of the proposed algorithm are demonstrated by examples.

The data center network (DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.

Cloud computing is deemed the next-generation information technology (IT) platform, in which a data center is crucial for providing a large amount of computing and storage resources for various service applications with high quality guaranteed. However, cloud users no longer possess their data in a local data storage infrastructure, which would result in auditing for the integrity of outsourced data being a challenging problem, especially for users with constrained computing resources. Therefore, how to help the users complete the verification of the integrity of the outsourced data has become a key issue. Public verification is a critical technique to solve this problem, from which the users can resort to a third-party auditor (TPA) to check the integrity of outsourced data. Moreover, an identity-based (ID-based) public key cryptosystem would be an efficient key management scheme for certificate-based public key setting. In this paper, we combine ID-based aggregate signature and public verification to construct the protocol of provable data integrity. With the proposed mechanism, the TPA not only verifies the integrity of outsourced data on behalf of cloud users, but also alleviates the burden of checking tasks with the help of users’ identity. Compared to previous research, the proposed scheme greatly reduces the time of auditing a single task on the TPA side. Security analysis and performance evaluation results show the high efficiency and security of the proposed scheme.