Shape registration is fundamental to 3D object acquisition; it is used to fuse scans from multiple views. Existing algorithms mainly utilize geometric information to determine alignment, but this typically results in noticeable misalignment of textures (i.e. surface colors) when using RGB-depth cameras. We address this problem using a novel approach to color-aware registration, which takes both color and geometry into consideration simultaneously. Color information is exploited throughout the pipeline to provide more effective sampling, correspondence and alignment, in particular for surfaces with detailed textures. Our method can furthermore tackle both rigid and non-rigid registration problems (arising, for example, due to small changes in the object during scanning, or camera distortions). We demonstrate that our approach produces significantly better results than previous methods.

In this paper, we propose a data-driven approach for realistic deformation of articulated meshes: the wide availability of pose data makes such an approach feasible. We use multiple reference models, combined with a fast linear blending skinning (LBS) method in local spaces. By exploiting information from the reference models, realistic deformation is achieved, yet with computational efficiency comparable to traditional blending methods-our approach is suitable for real-time applications. We demonstrate the effectiveness of our algorithm using various examples.

This paper introduces a scalable I/O model of Lustre file system and propose a dynamic I/O congestion control mechanism to support the incoming exascale HPC systems. Under its control, clients are allowed to issue more concurrent I/O requests to servers, which optimizes the utilization of the network/server resources and improves the I/O throughput, when servers are under light load; on the other hand, it can throttle the clients' I/O and limit the number of I/O requests queued on the server to control the I/O latency and avoid congestive collapse, when the server is overloaded. The results of series of experiments demonstrate the effectiveness of our congestion control mechanism. It prevents the occurrence of congestive collapse and on this premise it can maximize the I/O throughput for the scalable Lustre file system.

As the energy consumption of multi-core systems becomes increasingly prominent, it's a challenge to design an energy-efficient real-time scheduling algorithm in multi-core systems for reducing the system energy consumption while guaranteeing the feasibility of real-time tasks. In this paper, we focus on multi-core processors, with the global Dynamic Voltage Frequency Scaling (DVFS) and Dynamic Power Management (DPM) technologies. In this setting, we propose an energy-efficient real-time scheduling algorithm, the Time Local remaining execution plane based Dynamic Voltage Frequency Scaling (TL-DVFS). TL-DVFS utilizes the concept of Time Local remaining execution (TL) plane to dynamically scale the voltage and frequency of a processor at the initial time of each TL plane as well as at the release time of a sporadic task in each TL plane. Consequently, TL-DVFS can obtain a reasonable tradeoff between the real-time constraint and the energy-saving while realizing the optimal feasibility of sporadic tasks. Mathematical analysis and extensive simulations demonstrate that TL-DVFS always saves more energy than existing algorithms, especially in the case of high workloads, and guarantees the optimal feasibility of sporadic tasks at the same time.

As the energy consumption of embedded multiprocessor systems becomes increasingly prominent, the real-time energy-efficient scheduling in multiprocessor systems becomes an urgent problem to reduce the system energy consumption while meeting real-time constraints. For a multiprocessor with independent DVFS and DPM at each processor, this paper proposes an energy-efficient real-time scheduling algorithm named LRE-DVFS-EACH, based on LRE-TL which is an optimal real-time scheduling algorithm for sporadic tasks. LRE-DVFS-EACH utilizes the concept of TL plane and the idea of fluid scheduling to dynamically scale the voltage and frequency of processors at the initial time of each TL plane as well as the release time of a sporadic task in each TL plane. Consequently, LRE-DVFS-EACH can obtain a reasonable tradeoff between the real-time constraints and the energy saving. LRE-DVFS-EACH is also adaptive to the change of workload caused by the dynamic release of sporadic tasks, which can obtain more energy savings. The experimental results show that compared with existing algorithms, LRE-DVFS-EACH can not only guarantee the optimal feasibility of sporadic tasks, but also achieve more energy savings in all cases, especially in the case of high workloads.

We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters. Local non-rigid registration is posed in terms of minimising an energy functional, for which we give a closed-form linear system and solve it using an improved iterative Gauss-Seidel method. Our approach can consistently produce smooth and continuous registration fields, and correctly establish dense one-to-one correspondences. It can naturally deal with both open partial and closed shapes, and imperfect models with gaps and noise, through its use of the implicit vector representation. Experimental results on several datasets demonstrate the robustness of the proposed method.

In this paper, we propose a new algorithm for dynamic voltage scaling (DVS) based on feedback control mechanism. Besides handling a periodic tasks, our algorithm significantly reduces the energy consumption of periodic tasks and consequently the energy consumption of the whole task set. The results show that, comparing to on-line dynamic voltage scaling (the best algorithm to our knowledge), our approach improves the energy savings by 10% on most task sets tested and by 5% on average.

Abstract We consider the problem of approximating an arbitrary generic surface with a given set of simple surface primitives. In contrast to previous approaches based on variational surface approximation, which are primarily concerned with finding an optimal partitioning of the input geometry, we propose to integrate a model selection step into the algorithm in order to also optimize the type of primitive for each proxy. Our method is a joint global optimization of both the partitioning of the input surface as well as the types and number of used shape proxies. Thus, our method performs an automatic trade‐off between representation complexity and approximation error without relying on a user supplied predetermined number of shape proxies. This way concise surface representations are found that better exploit the full approximative power of the employed primitive types.

The effort of on-the-fly accessing 3D contents over the Internet has been done in recent years. And 3D streaming has been investigated to represent 3D models in the compact format and progressively transmit them on the limited-bandwidth and lossy channel. In the paper, an error resilient 3D mesh coding algorithm is presented, which employs an extended multiple quantization (EMQ) arithmetic coder method, inspired by the error-resilient JPEG 2000 image coding standards. With periodic arithmetic coder restarting and termination markers, the error resilient EMQ coder divides bit stream into little independent parts and enables basic transmission error containment. Furthermore, the EMQ coder has the intrinsic capacity of handling noise by using the maximum a posteriori (MAP) decoder. Experiments show that the method improves the mesh transmission quality in a simulated network environment.

This work considers the area coverage problem in wireless sensor networks with any arbitrary sensing shape. The task is to find the weak sub-regions deteriorating the overall coverage performance. By transforming the area coverage problem to the intersection points and vertices' coverage problem, we present an approach to evaluating and improving the performance of the coverage.

On the basis of minima rule from the cognitive theory, this paper presents an algorithm decomposing a mesh into smaller parts by feature contours, gotten from the minima negative curvature vertices. The algorithm is carried out in two steps. Firstly, to avoid over-segmentation, our method excludes unimportant local adjacent similar contours. Secondly, the remnant salient contours are automatically completed to form short loops around mesh's parts, constrained by two near parallel cutting planes that are determined by principal component analysis of all vertices. The algorithm has been demonstrated on many meshes, and the results show that it not only can perceptual group the adjacent self-similarity regions, but also can achieve reasonable segmentations.

A novel image steganography algorithm in wavelet domain is presented using the iterative blending method. Using this algorithm, we can hide a secret image with 256 gray levels into another carrier image. By taking full advantage of the masking characteristics of the human visual system, a JND (just noticeable difference) threshold matrix is given pixel by pixel in the image subbands taking into account the texture and the luminance content of carrier image. The secret image is divided into two matrices to make the gray level no more than 16. Then the matrices are adaptively embedded into the wavelet coefficients of the carrier image by iterative blending. The carrier image and the blending parameter can act as the private keys. The experimental results show that the proposed algorithm provides good transparency and is robust to some extent. The technique also can be used in digital watermarking and other digital application areas.