A low bit-rate video-coding algorithm based upon variable pattern selection

Recent research into pattern representation of moving regions in blocked-based motion estimation and compensation in video sequences, has focused mainly upon using a fixed number of regular shaped patterns. These are used to match the macroblocks in a frame that have two distinct regions involving static background and moving objects. In this paper a new Variable Pattern Selection (VPS) algorithm is presented which selects a preset number of best-matched patterns from a pattern codebook of regular shaped patterns. While more patterns are used than in the previous work, the performance of the VPS algorithm in using variable length coding, by exploiting the frequency of the best-matched patterns, leads to a higher compression ratio, without degrading the overall image quality

Fast Computation of the Fitness Function for Protein Folding Prediction in a 2D Hydrophobic-Hydrophilic Model

Protein Folding Prediction (PFP) is essentially an energy minimization problem formalised by the definition of a fitness function. Several PFP models have been proposed including the Hydrophobic-Hydrophilic (HP) model, which is widely used as a test-bed for evaluating new algorithms. The calculation of the fitness is the major computational task in determining the native conformation of a protein in the HP model and this paper presents a new efficient search algorithm (ESA) for deriving the fitness value requiring only O(n) complexity in contrast to the full search approach, which takes O(n2). The improved efficiency of ESA is achieved by exploiting some intrinsic properties of the HP model, with a resulting reduction of more than 50% in the overall time complexity when compared with the previously reported Caching Approach, with the added benefit that the additional space complexity is linear instead of quadratic

TVL₁shape approximation from scattered 3D data

With the emergence in 3D sensors such as laser scanners and 3D reconstruction from cameras, large 3D point clouds can now be sampled from physical objects within a scene. The raw 3D samples delivered by these sensors however, contain only a limited degree of information about the environment the objects exist in, which means that further geometrical high-level modelling is essential. In addition, issues like sparse data measurements, noise, missing samples due to occlusion, and the inherently huge datasets involved in such representations makes this task extremely challenging. This paper addresses these issues by presenting a new 3D shape modelling framework for samples acquired from 3D sensor. Motivated by the success of nonlinear kernel-based approximation techniques in the statistics domain, existing methods using radial basis functions are applied to 3D object shape approximation. The task is framed as an optimization problem and is extended using non-smooth L1 total variation regularization. Appropriate convex energy functionals are constructed and solved by applying the Alternating Direction Method of Multipliers approach, which is then extended using Gauss-Seidel iterations. This significantly lowers the computational complexity involved in generating 3D shape from 3D samples, while both numerical and qualitative analysis confirms the superior shape modelling performance of this new framework compared with existing 3D shape reconstruction techniques

Bandwidth Borrowing Schemes for Instantaneous Video-on-Demand Systems

A controlled multicast scheme provides instantaneous service, but limited server bandwidth causes some user requests to be either delayed or rejected when insufficient free bandwidth is available. Two borrowing schemes are proposed for instantaneous video-on-demand (VOD) that reduce the user request blocking rate by borrowing bandwidth from ongoing video streams when there is insufficient free bandwidth for the server to deliver a new video stream. Both these new schemes have proved to be successful in reducing blocking rate and increasing bandwidth utilization at the expense of temporarily degrading the video quality

Gestalt Theory in Visual Screen Design — A New Look at an old subject

Although often presented as a single basis for educational visual screen design, Gestalt theory is not a single small set of visual principles uniformly applied by all designers. In fact, it appears that instructional visual design literature often deals with only a small set of Gestalt laws. In this project Gestalt literature was consulted to distil the most relevant Gestalt laws for educational visual screen design. Eleven laws were identified. They deal with balance/symmetry, continuation, closure, figure-ground, focal point, isomorphic correspondence, prŠgnanz, proximity, similarity, simplicity, and unity/harmony. To test the usefulness of these laws in visual screen design they were applied to the redesign of an instructional multimedia application, 'WoundCare', designed to teach nursing students wound management. The basic text-based screens in the original WoundCare application were replaced with graphical user interface screens, that were designed according to these principles. The new screen designs were then evaluated by asking students and others to compare the designs. The viewers were also asked to rate directly the value of using the eleven Gestalt design principles in the redesign, both for improving the product's appearance and improving its value for learning. The evaluation results were overwhelmingly positive. Both the new design and the value of applying the eleven Gestalt laws to improve learning were strongly supported by the students' opinions. However, some differences in the value of applying particular Gestalt laws to the interface design were identified and this forms a useful direction for future research

Optimization of satellite altimeter and wave height measurements

Two techniques for simultaneously estimating altitude, ocean wave height, and signal-to-noise ratio from the GEOS-C satellite altimeter data are described. One technique was based on maximum likelihood estimation, MLE, and the other on minimum mean square error estimation, MMSE. Performance was determined by comparing the variance and bias of each technique with the variance and bias of the smoothed output from the Geos altimeter tracker. Ocean wave height tracking performance for the MLE and MMSE algorithms was measured by comparing the variance and bias of the wave height estimates with that of the expression for the return waveform obtained by a fit to the average output of the 16 waveform sampling gates

Technical guidance and analytic services in support of SEASAT-A

The design of a high resolution radar for altimetry and ocean wave height estimation was studied. From basic principles, it is shown that a short pulse wide beam radar is the most appropriate and recommended technique for measuring both altitude and ocean wave height. To achieve a topographic resolution of + or - 10 cm RMS at 5.0 meter RMS wave heights, as required for SEASAT-A, it is recommended that the altimeter design include an onboard adaptive processor. The resulting design, which assumes a maximum likelihood estimation (MLE) processor, is shown to satisfy all performance requirements. A design summary is given for the recommended radar altimeter, which includes a full deramp STRETCH pulse compression technique followed by an analog filter bank to separate range returns as well as the assumed MLE processor. The feedback loop implementation of the MLE on a digital computer was examined in detail, and computer size, estimation accuracies, and bias due to range sidelobes are given for the MLE with typical SEASAT-A parameters. The standard deviation of the altitude estimate was developed and evaluated for several adaptive and nonadaptive split-gate trackers. Split-gate tracker biases due to range sidelobes and transmitter noise are examined. An approximate closed form solution for the altimeter power return is derived and evaluated. The feasibility of utilizing the basic radar altimeter design for the measurement of ocean wave spectra was examined

Fuzzy image segmentation of generic shaped clusters

The segmentation performance of any clustering algorithm is very sensitive to the features in an image, which ultimately restricts their generalisation capability. This limitation was the primary motivation in our investigation into using shape information to improve the generality of these algorithms. Fuzzy shape-based clustering techniques already consider ring and elliptical profiles in segmentation, though most real objects are neither ring nor elliptically shaped. This paper addresses this issue by introducing a new shape-based algorithm called fuzzy image segmentation of generic shaped clusters (FISG) that incorporates generic shape information into the framework of the fuzzy c-means (FCM) algorithm. Both qualitative and quantitative analyses confirm the superiority of FISG compared to other shape-based fuzzy clustering methods including, Gustafson-Kessel algorithm, ring-shaped, circular shell, c-ellipsoidal shells and elliptic ring-shaped clusters. The new algorithm has also been shown to be application independent so it can be applied in areas such as video object plane segmentation in MPEG-4 based coding

A novel approach to the design of DSP systems using minimum complexity Finite State Machines

The paper presents a new and different approach to the design and realisation of Digital Signal Processing (DSP)systems by utilising Finite State Machines (FSM). The DSP system is modelled by mapping all its potential states into an FSM, whose complexity is usually very high. The FSM mirrors the complete functionality of the system and thus describes its behaviour in full detail. Examples for FSMs of first and second order digital recursive filters are provided and the current version of the software simulating the FSM corresponding to any linear time-invariant DSP system is described. The potential of this approach including state reduction techniques as well as the inclusion of non-linear DSP systems is also outlined, and further future research intentions are briefly explored

FollowMe: A Bigraphical Approach

In this paper we illustrate the use of modelling techniques using bigraphs to specify and refine elementary aspects of the FollowMe framework. This framework provides the seamless migration of bi-directional user interfaces for users as they navigate between zones within an intelligent environment