Image-Dependent Spatial Shape-Error Concealment

Existing spatial shape-error concealment techniques are broadly based upon either parametric curves that exploit geometric information concerning a shape's contour or object shape statistics using a combination of Markov random fields and maximum a posteriori estimation. Both categories are to some extent, able to mask errors caused by information loss, provided the shape is considered independently of the image/video. They palpably however, do not afford the best solution in applications where shape is used as metadata to describe image and video content. This paper presents a novel image-dependent spatial shape-error concealment (ISEC) algorithm that uses both image and shape information by employing the established rubber-band contour detecting function, with the novel enhancement of automatically determining the optimal width of the band to achieve superior error concealment. Experimental results corroborate both qualitatively and numerically, the enhanced performance of the new ISEC strategy compared with established techniques

A Bezier curve-based generic shape encoder

Existing Bezier curve based shape description techniques primarily focus upon determining a set of pertinent Control Points (CP) to represent a particular shape contour. While many different approaches have been proposed, none adequately consider domain specific information about the shape contour like its gradualness and sharpness, in the CP generation process which can potentially result in large distortions in the object’s shape representation. This paper introduces a novel Bezier Curve-based Generic Shape Encoder (BCGSE) that partitions an object contour into contiguous segments based upon its cornerity, before generating the CP for each segment using relevant shape curvature information. In addition, while CP encoding has generally been ignored, BCGSE embeds an efficient vertex-based encoding strategy exploiting the latent equidistance between consecutive CP. A nonlinear optimisation technique is also presented to enable the encoder is automatically adapt to bit-rate constraints. The performance of the BCGSE framework has been rigorously tested on a variety of diverse arbitrary shapes from both a distortion and requisite bit-rate perspective, with qualitative and quantitative results corroborating its superiority over existing shape descriptors

Geometric distortion measurement for shape coding: a contemporary review

Geometric distortion measurement and the associated metrics involved are integral to the rate-distortion (RD) shape coding framework, with importantly the efficacy of the metrics being strongly influenced by the underlying measurement strategy. This has been the catalyst for many different techniques with this paper presenting a comprehensive review of geometric distortion measurement, the diverse metrics applied and their impact on shape coding. The respective performance of these measuring strategies is analysed from both a RD and complexity perspective, with a recent distortion measurement technique based on arc-length-parameterisation being comparatively evaluated. Some contemporary research challenges are also investigated, including schemes to effectively quantify shape deformation

Object recognition in infrared imagery using appearance-based methods

Abstract unavailable please refer to PD

Ecology of a landscape-scale deer assemblage

This thesis investigates the ecology of a multi-species ungulate assemblage and their impacts to inform management in commercial forestry (Thetford Forest, eastern England, 195km2). The aims were to analyse environmental factors influencing deer densities, to identify the species causing the greatest damage to young crop plantings, and to analyse how habitat, landscape context and intra- and inter-specific competition affect roe deer performance. Local roe and muntjac densities (collected in 2018) were related to habitat, landscape context and recreation. Roe deer densities were higher in young (0-5 since planting) stands and lower closer to grasslands and in areas of high recreational activity. Muntjac densities were higher in mature (≥46 years) stands, on calcareous soils, and with high recreation, while being lower closer to grasslands. Effects of local species-specific densities (from 2018 to 2020) of muntjac, roe, fallow deer and large deer (comprising fallow and red deer) on scots pine (Pinus sylvestris) leader browsing were assessed while controlling for hares presence and ground vegetation. More pine leaders were browsed in localities with higher densities of fallow or ‘large’ deer. Using a long-term dataset (2002-2015) we analysed effects of habitat and landscape context on roe deer fertility and body mass. Yearling and adult roe deer were more fertile when heavier; adult body mass was higher closer to arable lands, however, adult fertility was lower closer to arable. Relative importance of intra- and interspecific competition of fallow deer and muntjac on the condition and fertility of adult roe deer was tested using data from 2011-2016. Densities of muntjac were negatively related to fallow deer densities. Roe deer fertility was lower at higher muntjac densities, while being higher at higher roe deer densities. Roe deer are, therefore, subject to inter-specific competition from muntjac while intra-specific competition wasn’t detected. This is among the first studies showing effects of inter-specific competition of introduced species on reproductive output of a native vertebrate. Deer management should focus on reducing large deer and introduced species numbers to reduce impacts on regeneration and alleviate interspecific competition on native roe

Virtual Motion Camouflage Based Nonlinear Constrained Optimal Trajectory Design Method

Nonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance in numerous fields. Many attempts have been made to present new methods that can solve for optimal trajectories more efficiently or to improve the overall performance of existing techniques. This research presents a recently developed bio-inspired method called the Virtual Motion Camouflage (VMC) method that offers a means of quickly finding, within a defined but varying search space, the optimal trajectory that is equal or close to the optimal solution. The research starts with the polynomial-based VMC method, which works within a search space that is defined by a selected and fixed polynomial type virtual prey motion. Next will be presented a means of improving the solution’s optimality by using a sequential based form of VMC, where the search space is adjusted by adjusting the polynomial prey trajectory after a solution is obtained. After the search space is adjusted, an optimization is performed in the new search space to find a solution closer to the global space optimal solution, and further adjustments are made as desired. Finally, a B-spline augmented VMC method is presented, in which a B-spline curve represents the prey motion and will allow the search space to be optimized together with the solution trajectory. It is shown that (1) the polynomial based VMC method will significantly reduce the overall problem dimension, which in practice will significantly reduce the computational cost associated with solving nonlinear constrained optimal trajectory problems; (2) the sequential VMC method will improve the solution optimality by sequentially refining certain parameters, such as the prey motion; and (3) the B-spline augmented VMC method will improve the solution iv optimality without sacrificing the CPU time much as compared with the polynomial based approach. Several simulation scenarios, including the Breakwell problem, the phantom track problem, the minimum-time mobile robot obstacle avoidance problem, and the Snell’s river problem are simulated to demonstrate the capabilities of the various forms of the VMC algorithm. The capabilities of the B-spline augmented VMC method are also shown in a hardware demonstration using a mobile robot obstacle avoidance testbed

Proceedings, MSVSCC 2015

The Virginia Modeling, Analysis and Simulation Center (VMASC) of Old Dominion University hosted the 2015 Modeling, Simulation, & Visualization Student capstone Conference on April 16th. The Capstone Conference features students in Modeling and Simulation, undergraduates and graduate degree programs, and fields from many colleges and/or universities. Students present their research to an audience of fellow students, faculty, judges, and other distinguished guests. For the students, these presentations afford them the opportunity to impart their innovative research to members of the M&S community from academic, industry, and government backgrounds. Also participating in the conference are faculty and judges who have volunteered their time to impart direct support to their students’ research, facilitate the various conference tracks, serve as judges for each of the tracks, and provide overall assistance to this conference. 2015 marks the ninth year of the VMASC Capstone Conference for Modeling, Simulation and Visualization. This year our conference attracted a number of fine student written papers and presentations, resulting in a total of 51 research works that were presented. This year’s conference had record attendance thanks to the support from the various different departments at Old Dominion University, other local Universities, and the United States Military Academy, at West Point. We greatly appreciated all of the work and energy that has gone into this year’s conference, it truly was a highly collaborative effort that has resulted in a very successful symposium for the M&S community and all of those involved. Below you will find a brief summary of the best papers and best presentations with some simple statistics of the overall conference contribution. Followed by that is a table of contents that breaks down by conference track category with a copy of each included body of work. Thank you again for your time and your contribution as this conference is designed to continuously evolve and adapt to better suit the authors and M&S supporters. Dr.Yuzhong Shen Graduate Program Director, MSVE Capstone Conference Chair John ShullGraduate Student, MSVE Capstone Conference Student Chai