A robust motion estimation with center-biased diamond search and its parallel architecture for motion-compensated de-interlace

For motion compensated de-interlace, the accuracy and reliability of the motion vectors have a significant impact on the performance of the motion compensated interpolation. In order to improve the robustness of motion vector, a novel motion estimation algorithm with center-biased diamond search and its parallel VLSI architecture are proposed in this paper. Experiments show that it works better than conventional motion estimation algorithms in terms of motion compensation error and robustness, and its architecture overcomes the irregular data flow and achieves high efficiency. It also efficiently reuses data and reduces the control overhead. So, it is highly suitable for HDTV applications.     

Output feedback robust MPC for LPV system with polytopic model parametric uncertainty and bounded disturbance

The output feedback robust model predictive control (MPC), for the linear parameter varying (LPV) system with norm-bounded disturbance, is addressed, where the model parametric matrices are only known to be bounded within a polytope. The previous techniques of norm-bounding technique, quadratic boundedness (QB), dynamic output feedback, and ellipsoid (true-state bound; TSB) refreshment formula for guaranteeing recursive feasibility, are fused into the newly proposed approaches. In the notion of QB, the full Lyapunov matrix is applied for the first time in this context. The single-step dynamic output feedback robust MPC, where the infinite-horizon control moves are parameterised as a dynamic output feedback law, is the main topic of this paper, while the multi-step method is also suggested. In order to strictly guarantee the physical constraints, the outer bound of the true state replaces the true state itself, so tightness of this bound has a major effect on the control performance. In order to tighten the TSB, a procedure for refreshing the real-time ellipsoid based on that of the last sampling instant is given. This paper is conclusive for the past results and far-reaching for the future researches. Two benchmark examples are given to show the effectiveness of the novel results.     

Leader-follower consensus control of Lipschitz nonlinear systems by output feedback

This paper deals with the leader-follower consensus problem of Lipschitz nonlinear systems under fixed directed communication networks. Both state and output feedback control are proposed based on state and output measurements of neighbouring agents, respectively. Laplacian matrix features are explored for the stability analysis, and the sufficient conditions are derived to solve the consensus problem. Finally, simulation results are included to demonstrate the effectiveness of the output-based consensus controller.     

Activity recognition and intensity estimation in youth from accelerometer data aided by machine learning

Physical activity monitoring for youth is an area of increasing scientific and public health interest due to the high prevalence of obesity and downward trend in physical activity. However, accurate assessment of such activity remains a challenging problem because of the complex nature in which certain activities are performed. In this study, we formulated the issue as a machine learning problem—using a diverse set of 19 physical activities commonly performed by youth—via two approaches: activity recognition and intensity estimation. With the aid of training data, we implemented a distance metric learning method called DML-KNN that utilizes time-frequency features and is capable of effectively classifying both continuous and intermittent movement in youth subjects. Four different time-frequency feature extraction methods were then systematically evaluated. Our results show that the DML-KNN method performed competitively, especially when using features extracted by the Tamura method for intensity estimation, and by the Square Coefficient method for activity recognition.     

Accelerated Manhattan hashing via bit-remapping with location information

Multimedia Tools and Applications - Hashing is a binary-code encoding method which tries to preserve the neighborhood structures in the original feature space, in order to realize efficient...     

RFID触控屏幕点餐系统

餐饮行业的传统书面方式及定点式系统点餐服务方式已经不能满足人们生活水平日益提高的需求。结合RFID卡及卡片阅读机,利用Visual Basic作为前台开发工具,以Socket建立TCP联机并以此来传输数据,利用Access建立后台数据库开发并完成了RFID触控屏幕点餐系统[1]。     

Real time 3D simulation for nose surgery and automatic individual prosthesis design

This paper presents an intuitive nose surgery planning and simulation system, using 3D laser scan image and lateral X-ray image, to provide high quality prediction of the postoperative appearance, and design the patient specific prosthesis model automatically. After initial registration, the internal surface of soft tissue at the nose region was generated by the statistical data for soft tissue thickness adapted by the individual thickness information from the X-ray image. Then, the sketch contour of the 3D scan data on the lateral X-ray image was modified manually or adjusted automatically according to some aesthetic statistical data, to drive the simulation in real time by the state-of-the-art Laplacian surface deformation method. When satisfied with the 3D postoperative appearance, the deformation was mapped to the internal surface of soft tissue, and the change before and after simulation was utilized to generate the patient specific prosthesis model automatically. The surgeons who used the system confirmed that this planning system is attractive and has potential for daily clinical practice.     

3D finite element mesh generation of complicated tooth model based on CT slices

An interactive three-dimensional finite element generation method is presented for modelling a multi-connected teeth and mandible structure. The tetrahedron is chosen as the basic element type due to its rigorous adaptability to structures with geometric complexities. The mesh generation is implemented by allocating two quadrangles in adjacent CT image slices to form a set of tetrahedrons. By examining all the possible allocations and their degradations, an algorithm is developed for interactive mesh generation, resulting in a series of tetrahedrons consistent with all the others without overlapping and spacing. The developed system was applied to a tooth-mandibular structure, generating a complicated 3D FEM model consisting of 4762 nodes and 18,534 tetrahedral elements with nine different materials. This 3D model was successfully used to evaluate different tooth restoration strategies, which proved the viability and effectiveness of the proposed method.