Localization and Positioning Using Combinations of Model Views

A method for localization and positioning in an indoor environment is presented. The method is based on representing the scene as a set of 2D views and predicting the appearances of novel views by linear combinations of the model views. The method is accurate under weak perspective projection. Analysis of this projection as well as experimental results demonstrate that in many cases it is sufficient to accurately describe the scene. When weak perspective approximation is invalid, an iterative solution to account for the perspective distortions can be employed. A simple algorithm for repositioning, the task of returning to a previously visited position defined by a single view, is derived from this method.

Pose-Invariant Face Recognition Using Real and Virtual Views

The problem of automatic face recognition is to visually identify a person in an input image. This task is performed by matching the input face against the faces of known people in a database of faces. Most existing work in face recognition has limited the scope of the problem, however, by dealing primarily with frontal views, neutral expressions, and fixed lighting conditions. To help generalize existing face recognition systems, we look at the problem of recognizing faces under a range of viewpoints. In particular, we consider two cases of this problem: (i) many example views are available of each person, and (ii) only one view is available per person, perhaps a driver's license or passport photograph. Ideally, we would like to address these two cases using a simple view-based approach, where a person is represented in the database by using a number of views on the viewing sphere. While the view-based approach is consistent with case (i), for case (ii) we need to augment the single real view of each person with synthetic views from other viewpoints, views we call 'virtual views'. Virtual views are generated using prior knowledge of face rotation, knowledge that is 'learned' from images of prototype faces. This prior knowledge is used to effectively rotate in depth the single real view available of each person. In this thesis, I present the view-based face recognizer, techniques for synthesizing virtual views, and experimental results using real and virtual views in the recognizer.

‘Novice Teachers’ Views of an Introductory Workshop about Teaching in the Biosciences.

Seven regional networking events, aimed at supporting and developing ‘early stage’ novice university bioscience teachers were held across the UK. These workshops allowed 230 participants to reflect on teaching styles, learn about Higher Education Academy resources and discuss strategies to deal with a range of teaching situations. Post-event feedback was sought, and the results are presented in this paper. Feedback on the events was overwhelmingly positive, highlighting the need for such events to support the development of new teachers in higher education. Institutional training varies and these opportunities for sharing experiences, asking questions, networking and reflection on teaching practice were highly regarded. Most participants felt more confident about their teaching and believed that students were more directly engaged in their teaching after attending the events. Recommendations for support of this category of teacher include provision of discipline-specific events, opportunity for local area networking and support for the development of reflective practice in teaching and learning.

Trends in use of electronic journals in higher education in the UK - views of academic staff and students

Bonthron, Karen; Urquhart, Christine; Thomas, Rhian; Armstrong, Chris; Ellis, David; Everitt, Jean; Fenton, Roger; Lonsdale, Ray; McDermott, Elizabeth; Morris, Helen; Phillips, Rebecca; Spink, Sian, and Yeoman, Alison. (2003, June). Trends in use of electronic journals in higher education in the UK - views of academic staff and students. D-Lib Magazine, 9(6). Retrieved September 8, 2006 from http://www.dlib.org/dlib/june03/urquhart/06urquhart.html This item is freely available online at http://www.dlib.org/dlib/june03/urquhart/06urquhart.html Sponsorship: JISC

The Net and the Self: Colliding Views of Individuality and Nationhood in the Pre-Devolutionary plays of Mark Jenkins and Ed Thomas

Owen, Roger, 'The Net and the Self: Colliding Views of Individuality and Nationhood in the Pre-Devolutionary plays of Mark Jenkins and Ed Thomas', In: 'Cool Britannia: British Political Drama in the 1990s', Rebecca D'Mont? and Graham Saunders (eds), (Basingstoke: Palgrave Macmillan), pp.158-175, 2007 RAE2008

Gates, beads and Danubians. The defences and garrison of the auxiliary fort at Castell Collen: a speculative relationship

Davies, Jeffrey, 'Gates, beads and Danubians. The defences and garrison of the auxiliary fort at Castell Collen: a speculative relationship', Bayerische Vorgeschichtsblatter (2006) 71 pp.3-13 RAE2008

Physically-Based Combinations of Views: Representing Rigid and Nonrigid Motion

Nonrigid motion can be described as morphing or blending between extremal shapes, e.g., heart motion can be described as transitioning between the systole and diastole states. Using physically-based modeling techniques, shape similarity can be measured in terms of forces and strain. This provides a physically-based coordinate system in which motion is characterized in terms of physical similarity to a set of extremal shapes. Having such a low-dimensional characterization of nonrigid motion allows for the recognition and the comparison of different types of nonrigid motion.

Surface Reconstruction from Multiple Views using Rational B-Splines

A method for reconstructing 3D rational B-spline surfaces from multiple views is proposed. The method takes advantage of the projective invariance properties of rational B-splines. Given feature correspondences in multiple views, the 3D surface is reconstructed via a four step framework. First, corresponding features in each view are given an initial surface parameter value (s; t), and a 2D B-spline is fitted in each view. After this initialization, an iterative minimization procedure alternates between updating the 2D B-spline control points and re-estimating each feature's (s; t). Next, a non-linear minimization method is used to upgrade the 2D B-splines to 2D rational B-splines, and obtain a better fit. Finally, a factorization method is used to reconstruct the 3D B-spline surface given 2D B-splines in each view. This surface recovery method can be applied in both the perspective and orthographic case. The orthographic case allows the use of additional constraints in the recovery. Experiments with real and synthetic imagery demonstrate the efficacy of the approach for the orthographic case.

3D Hand Pose Estimation by Finding Appearance-Based Matches in a Large Database of Training Views

Ongoing work towards appearance-based 3D hand pose estimation from a single image is presented. A large database of synthetic hand views is generated using a 3D hand model and computer graphics. The views display different hand shapes as seen from arbitrary viewpoints. Each synthetic view is automatically labeled with parameters describing its hand shape and viewing parameters. Given an input image, the system retrieves the most similar database views, and uses the shape and viewing parameters of those views as candidate estimates for the parameters of the input image. Preliminary results are presented, in which appearance-based similarity is defined in terms of the chamfer distance between edge images.

Surface Reconstruction from Multiple Views using Rational B-Splines and Knot Insertion

A method for reconstruction of 3D rational B-spline surfaces from multiple views is proposed. Given corresponding features in multiple views, though not necessarily visible in all views, the surface is reconstructed. First 2D B-spline patches are fitted to each view. The 3D B-splines and projection matricies can then be extracted from the 2D B-splines using factorization methods. The surface fit is then further refined via an iterative procedure. Finally, a hierarchal fitting scheme is proposed to allow modeling of complex surfaces by means of knot insertion. Experiments with real imagery demonstrate the efficacy of the approach.

Tracking a Large Number of Objects from Multiple Views

We propose a multi-object multi-camera framework for tracking large numbers of tightly-spaced objects that rapidly move in three dimensions. We formulate the problem of finding correspondences across multiple views as a multidimensional assignment problem and use a greedy randomized adaptive search procedure to solve this NP-hard problem efficiently. To account for occlusions, we relax the one-to-one constraint that one measurement corresponds to one object and iteratively solve the relaxed assignment problem. After correspondences are established, object trajectories are estimated by stereoscopic reconstruction using an epipolar-neighborhood search. We embedded our method into a tracker-to-tracker multi-view fusion system that not only obtains the three-dimensional trajectories of closely-moving objects but also accurately settles track uncertainties that could not be resolved from single views due to occlusion. We conducted experiments to validate our greedy assignment procedure and our technique to recover from occlusions. We successfully track hundreds of flying bats and provide an analysis of their group behavior based on 150 reconstructed 3D trajectories.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.

Irish occupational therapists' views of electronic assistive technology

Introduction: Electronic assistive technology (EAT) includes computers, environmental control systems and information technology systems and is widely considered to be an important part of present-day life. Method: Fifty-six Irish community occupational therapists completed a questionnaire on EAT. All surveyed were able to identify the benefits of EAT. Results: While respondents reported that they should be able to assess for and prescribe EATs, only a third (19) were able to do so, and half (28) had not been able to do so in the past. Community occupational therapists identified themselves as havinga role in a multidisciplinary team to assess for and prescribe EAT. Conclusion: Results suggest that it is important for occupational therapists to have up-to-date knowledge and training in assistive and computer technologies in order to respond to the occupational needs of clients.

Specialist and primary care physicians' views on barriers to adequate preparation of patients for renal replacement therapy: a qualitative study.

BACKGROUND: Early preparation for renal replacement therapy (RRT) is recommended for patients with advanced chronic kidney disease (CKD), yet many patients initiate RRT urgently and/or are inadequately prepared. METHODS: We conducted audio-recorded, qualitative, directed telephone interviews of nephrology health care providers (n = 10, nephrologists, physician assistants, and nurses) and primary care physicians (PCPs, n = 4) to identify modifiable challenges to optimal RRT preparation to inform future interventions. We recruited providers from public safety-net hospital-based and community-based nephrology and primary care practices. We asked providers open-ended questions to assess their perceived challenges and their views on the role of PCPs and nephrologist-PCP collaboration in patients' RRT preparation. Two independent and trained abstractors coded transcribed audio-recorded interviews and identified major themes. RESULTS: Nephrology providers identified several factors contributing to patients' suboptimal RRT preparation, including health system resources (e.g., limited time for preparation, referral process delays, and poorly integrated nephrology and primary care), provider skills (e.g., their difficulty explaining CKD to patients), and patient attitudes and cultural differences (e.g., their poor understanding and acceptance of their CKD and its treatment options, their low perceived urgency for RRT preparation; their negative perceptions about RRT, lack of trust, or language differences). PCPs desired more involvement in preparation to ensure RRT transitions could be as "smooth as possible", including providing patients with emotional support, helping patients weigh RRT options, and affirming nephrologist recommendations. Both nephrology providers and PCPs desired improved collaboration, including better information exchange and delineation of roles during the RRT preparation process. CONCLUSIONS: Nephrology and primary care providers identified health system resources, provider skills, and patient attitudes and cultural differences as challenges to patients' optimal RRT preparation. Interventions to improve these factors may improve patients' preparation and initiation of optimal RRTs.