Measuring reef complexity and rugosity from monocular video bathymetric reconstruction

Topographic structural complexity of a reef is highly correlated to coral growth rates, coral cover and overall levels of biodiversity, and is therefore integral in determining ecological processes. Modeling these processes commonly includes measures of rugosity obtained from a wide range of different survey techniques that often fail to capture rugosity at different spatial scales. Here we show that accurate estimates of rugosity can be obtained from video footage captured using underwater video cameras (i.e., monocular video). To demonstrate the accuracy of our method, we compared the results to in situ measurements of a 2m x 20m area of forereef from Glovers Reef atoll in Belize. Sequential pairs of images were used to compute fine scale bathymetric reconstructions of the reef substrate from which precise measurements of rugosity and reef topographic structural complexity can be derived across multiple spatial scales. To achieve accurate bathymetric reconstructions from uncalibrated monocular video, the position of the camera for each image in the video sequence and the intrinsic parameters (e.g., focal length) must be computed simultaneously. We show that these parameters can be often determined when the data exhibits parallax-type motion, and that rugosity and reef complexity can be accurately computed from existing video sequences taken from any type of underwater camera from any reef habitat or location. This technique provides an infinite array of possibilities for future coral reef research by providing a cost-effective and automated method of determining structural complexity and rugosity in both new and historical video surveys of coral reefs.

Bone tissue engineering : reconstruction of critical sized segmental bone defects in the ovine tibia

Well-established therapies for bone defects are restricted to bone grafts which face significant disadvantages (limited availability, donor site morbidity, insufficient integration). Therefore, the objective was to develop an alternative approach investigating the regenerative potential of medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) and silk-hydroxyapatite (silk-HA) scaffolds. Critical sized ovine tibial defects were created and stabilized. Defects were left untreated, reconstructed with autologous bone grafts (ABG) and mPCL-TCP or silk-HA scaffolds. Animals were observed for 12 weeks. X-ray analysis, torsion testing and quantitative computed tomography (CT) analyses were performed. Radiological analysis confirmed the critical nature of the defects. Full defect bridging occurred in the autograft and partial bridging in the mPCL-TCP group. Only little bone formation was observed with silk-HA scaffolds. Biomechanical testing revealed a higher torsional moment/stiffness (p < 0.05) and CT analysis a significantly higher amount of bone formation for the ABG group when compared to the silk-HA group. No significant difference was determined between the ABG and mPCL-TCP groups. The results of this study suggest that mPCL-TCP scaffolds combined can serve as an alternative to autologous bone grafting in long bone defect regeneration. The combination of mPCL-TCP with osteogenic cells or growth factors represents an attractive means to further enhance bone formation.

Silk fibroin in ocular surface reconstruction : what is its potential as a biomaterial in ophthalmics?

Hardly a month goes by within the scientific literature without some new material “X” being reported as a suitable material on which to grow cell type “Y”, for the potential purpose of treating disease “Z”. Thus when fibroin, a protein found in silk, was first proposed as a biomaterial for cell growth [1] it joined a long list of other materials of both natural as well as synthetic origin. Nevertheless, in the second decade of the Asian Century it is perhaps befitting that a material of so much importance to the continent’s cultural and economic history, should become the focus of cutting-edge biomedical research. Sentiments aside, however, silk fibroin possesses quite a unique combination of properties which make it a promising candidate for repairing the eye and especially for treating damage to the cornea, the transparent window at the front of the eye.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Cohort normalization based sparse representation for undersampled face recognition

Abstract. In recent years, sparse representation based classification(SRC) has received much attention in face recognition with multipletraining samples of each subject. However, it cannot be easily applied toa recognition task with insufficient training samples under uncontrolledenvironments. On the other hand, cohort normalization, as a way of mea-suring the degradation effect under challenging environments in relationto a pool of cohort samples, has been widely used in the area of biometricauthentication. In this paper, for the first time, we introduce cohort nor-malization to SRC-based face recognition with insufficient training sam-ples. Specifically, a user-specific cohort set is selected to normalize theraw residual, which is obtained from comparing the test sample with itssparse representations corresponding to the gallery subject, using poly-nomial regression. Experimental results on AR and FERET databases show that cohort normalization can bring SRC much robustness against various forms of degradation factors for undersampled face recognition.

General trajectory prior for non-rigid reconstruction

Trajectory basis Non-Rigid Structure From Motion (NRSFM) currently faces two problems: the limit of reconstructability and the need to tune the basis size for different sequences. This paper provides a novel theoretical bound on 3D reconstruction error, arguing that the existing definition of reconstructability is fundamentally flawed in that it fails to consider system condition. This insight motivates a novel strategy whereby the trajectory's response to a set of high-pass filters is minimised. The new approach eliminates the need to tune the basis size and is more efficient for long sequences. Additionally, the truncated DCT basis is shown to have a dual interpretation as a high-pass filter. The success of trajectory filter reconstruction is demonstrated quantitatively on synthetic projections of real motion capture sequences and qualitatively on real image sequences.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

Prostate gland and extra-capsular tissue 3D reconstruction and measurement

Currently there are little objective parameters that can quantify the success of one form of prostate surgical removal over another. Accordingly, at Old Dominion University (ODU) we have been developing a process resulting in the use of software algorithms to assess the coverage and depth of extra-capsular soft tissue removed with the prostate by the various surgical approaches. Parameters such as the percent of capsule that is bare of soft tissue and where present the depth and extent of coverage have been assessed. First, visualization methods and tools are developed for images of prostate slices that are provided to ODU by the Pathology Department at Eastern Virginia Medical School (EVMS). The visualization tools interpolate and present 3D models of the prostates. Measurement algorithms are then applied to determine statistics about extra-capsular tissue coverage. This paper addresses the modeling, visualization, and analysis of prostate gland tissue to aid in quantifying prostate surgery success. Particular attention is directed towards the accuracy of these measurements and is addressed in the analysis discussions.

Critical Factors for Sustainable Post Natural Disaster Reconstruction : Chinese Data

While scientists continue to explore the level of climate change impact to new weather patterns and our environment in general, there have been some devastating natural disasters worldwide in the last two decades. Indeed natural disasters are becoming a major concern in our society. Yet in many previous examples, our reconstruction efforts only focused on providing short-term necessities. How to develop resilience in the long run is now a highlight for research and industry practice. This paper introduces a research project aimed at exploring the relationship between resilience building and sustainability in order to identify key factors during reconstruction efforts. From extensive literature study, the authors considered the inherent linkage between the two issues as evidenced from past research. They found that sustainability considerations can improve the level of resilience but are not currently given due attention. Reconstruction efforts need to focus on resilience factors but as part of urban development, they must also respond to the sustainability challenge. Sustainability issues in reconstruction projects need to be amplified, identified, processed, and managed properly. On-going research through empirical study aims to establish critical factors (CFs) for stakeholders in disaster prone areas to plan for and develop new building infrastructure through holistic considerations and balanced approaches to sustainability. A questionnaire survey examined a range of potential factors and the subsequent data analysis revealed six critical factors for sustainable Post Natural Disaster Reconstruction that include: considerable building materials and construction methods, good governance, multilateral coordination, appropriate land-use planning and policies, consideration of different social needs, and balanced combination of long-term and short-term needs. Findings from this study should have an influence on policy development towards Post Natural Disaster Reconstruction and help with the achievement of sustainable objectives.

Autologous vs. allogenic mesenchymal progenitor cells for the reconstruction of critical-sized segmental tibial bone defects in aged sheep

Mesenchymal progenitor cells (MPCs) represent an attractive cell population for bone tissue engineering. Their special immunological characteristics suggest that MPCs may be used in an allogenic application. The objective of this study was to compare the regenerative potential of autologous vs. allogenic MPCs in an ovine critical-sized segmental defect model. Ovine MPCs were isolated from bone marrow aspirates, expanded and cultured with osteogenic media for two weeks before implantation. Autologous and allogenic transplantation was performed by using the cell-seeded scaffolds, unloaded scaffolds and the application of autologous bone grafts served as control groups (n=6). Bone healing was assessed twelve weeks after surgery by radiology, micro computed tomography, biomechanical testing and histology. Radiology, biomechanical testing and histology revealed no significant difference in bone formation between the autologous and allogenic group. Both cell groups showed more bone formation than the scaffold alone, whereas the biomechanical data showed no significant differences between the cell-groups and the unloaded scaffolds. The results of the study suggest that scaffold based bone tissue engineering using allogenic cells offers the potential for an off the shelf product. Therefore, the results of this study serve as an important baseline for the translation of the assessed concepts into clinical application.

Critical factors for successful housing reconstruction projects following a major disaster

Post–disaster reconstruction projects are often considered ineffectual or unproductive because on many occasions in the past they have performed extremely poorly during post-contract occupation, or have failed altogether to deliver acceptable outcomes. In some cases, these projects have already failed even before their completion, leading many sponsor aid organisations to hold these projects up as examples of how not to deliver housing reconstruction. Research into some previous unsuccessful projects has revealed that often the lack of adequate knowledge regarding the context and complexity involved in the implementation of these projects is generally responsible for their failure. Post-disaster reconstruction projects are certainly very complex in nature, often very context-specific and they can vary widely in magnitude. Despite such complexity, reconstruction projects can still have a high likelihood of success if adequate consideration is given to the importance of factors which are known to positively influence reconstruction efforts. Good outcomes can be achieved when planners and practitioners ensure best practices are embedded in the design of reconstruction projects at the time reconstruction projects they are first instigated. This paper outlines and discusses factors that significantly contribute to the successful delivery of post-disaster housing reconstruction projects.

Quantitative and qualitative assessment of the regenerative potential of osteoblasts versus bone marrow derived mesenchymal stem cells in the reconstruction of critical sized segmental tibial bone defects in a large animal model

This thesis is about the use of different cells for bone tissue engineering. The cells were used in combination with a novel biomaterial in a large tibial bone defects in a sheep model. Furthermore this study developed a novel cell delivery procedure for bone tissue engineering. This novel procedure of cell delivery could overcome the current problems of cell-based tissue engineering and serve as a baseline for the translation of novel concepts into clinical application.

Post-disaster reconstruction: a statistical overview of the barriers for community participation in Afghanistan

When a community already torn by an event such as a prolonged war, is then hit by a natural disaster, the negative impact of this subsequent disaster in the longer term can be extremely devastating. Natural disasters further damage already destabilised and demoralised communities, making it much harder for them to be resilient and recover. Communities often face enormous challenges during the immediate recovery and the subsequent long term reconstruction periods, mainly due to the lack of a viable community involvement process. In post-war settings, affected communities, including those internally displaced, are often conceived as being completely disabled and are hardly ever consulted when reconstruction projects are being instigated. This lack of community involvement often leads to poor project planning, decreased community support, and an unsustainable completed project. The impact of war, coupled with the tensions created by the uninhabitable and poor housing provision, often hinders the affected residents from integrating permanently into their home communities. This paper outlines a number of fundamental factors that act as barriers to community participation related to natural disasters in post-war settings. The paper is based on a statistical analysis of, and findings from, a questionnaire survey administered in early 2012 in Afghanistan.

Critical factors for sustainable reconstruction of post natural disasters

While scientists are still debating the level of climate change impact to new weather patterns, there have been some devastating natural disasters worldwide in the last decade. From cyclones to earthquakes and from Tsunamis to landslides, these disasters occur with formidable forces and crushing effects. As one of the most important arrangements to erase the negative influence of natural disasters and help with the recovery and redevelopment of the hit area, reconstruction is of utmost importance in light of sustainable objectives. However, current reconstruction practice confronts quite a lot of criticisms for focusing on providing short-term necessities. How to conduct the post disaster reconstruction in a long-term perspective and achieve sustainable development is thereby a highlight for industry practice and research. This paper introduced an on-going research project which is aimed at establishing an operational framework for improving sustainability performance of post disaster reconstruction by identifying critical sustainable factors and exploring their internal relationships. The research reported in this paper is part of the project. After a comprehensive literature review, 17 potential critical sustainability factors for post disaster reconstruction were identified. Preliminary examination and discussion of the factors was conducted.