303 research outputs found

    Visual tracking for sports applications

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    Visual tracking of the human body has attracted increasing attention due to the potential to perform high volume low cost analyses of motions in a wide range of applications, including sports training, rehabilitation and security. In this paper we present the development of a visual tracking module for a system aimed to be used as an autonomous instructional aid for amateur golfers. Postural information is captured visually and fused with information from a golf swing analyser mat and both visual and audio feedback given based on the golfer's mistakes. Results from the visual tracking module are presented

    Autonomous Sports Training from Visual Cues

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    Computer driven biometric analysis of athlete's movements have proven themselves as effective sports training tools. Most current systems rely on the use of retro-reflective markers or magnetic sensors to capture the motion of the athlete, so the biometric analysis can be performed. Video based training tools have also proved to be valuable instructional aids, however most require significant human interaction for analysis to be performed. This paper outlines an ongoing project focussed on capturing posture without the use of any markers or sensors, while still capturing enough information for an automated analysis to be performed. The approach taken to solving this problem is presented, as well as the current state of development of a an instructional aid for golfers

    Segmentation of Non-Stationary Signals with Applications

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    Non-stationary signals are partitioned into near stationary segments using a modified Appel and Brandt algorithms. The modification requires two spectral distance measures to be used to produce an algorithm which is insensitive to changes in signal energy level which are irrelevant in this application. Performance on real and simulated data is presented. Segmentation has been used to provide an estimator of the evolution spectrum and an application to a noisy communication signal is presented

    MIME: A Gesture-Driven Computer Interface

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    MIME (Mime Is Manual Expression) is a computationally efficient computer vision system for recognizing hand gestures. The system is intended to replace the mouse interface on a standard personal computer to control application in a more intuitive manner. The system is implemented in C code with no hardware-acceleration and tracks hand motion at 30 fps on a standard PC. Using a simple two-dimensional model of the human hand, MIME employs a highly-efficient, single-pass algorithm to segment the hand and extract its model parameters from each frame in the video input. The hand is tracked from one frame to the next using a constant-acceleration Kalman filter. Tracking and feature extraction is remarkably fast and robust even when the hand is placed above difficult backdrops such as a typical cluttered desktop environment. Because of the efficient coding of the gesture tracking, adequate CPU power remains to run standard applications such as web browsers and presentations

    A Multi-Resolution Algorithm for Cytological Image Segmentation

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    This paper propses a multi-resolution method for cell segmentation, and outlines some of the advantages it has over other techniques. The research is based on approach developed by Wilson and Spann, and the other paper details some improvements on this algorithm for this particular problem

    A Unified Approach to the STFT, TFDs and Instantaneous Frequency

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    Spectral analysis of time varying signals is traditionally performed with the short time Fourier transformation (STFT). In the last few years, many authors have advocated the use of time frequency distributions for this task. This paper has 2 main aims. The first is to reformulate Cohen-class of time frequency representations (TFRs) into discrete-time, discrete-frequency, computer-implemented form. The second aim is to show how, in this form, many of the properties of the continuous-time, continuous-frequency formulation are either lost or altered. Intuitions applicable in the continuous-time case examined here. The properties of the discrete variable formulation examined are the presence and form of cross-terms, instantaneous frequency (IF) estimation and relations between Cohen's class TFRs. We define a parameterized class of distributions which is a blending between the STFT and wigner ville distribution (WVD). The two main conclusions to be drawn are that all TFRs of Cohen's class implementable in the form (which includes all commonly used TFRs) posses cross terms and that IF estimation using periodic moments of these TFRs is purposeless, since simpler methods obtain the same results

    A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

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    This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added

    Bodies, technologies and action possibilities: when is an affordance?

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    Borrowed from ecological psychology, the concept of affordances is often said to offer the social study of technology a means of re-framing the question of what is, and what is not, ‘social’ about technological artefacts. The concept, many argue, enables us to chart a safe course between the perils of technological determinism and social constructivism. This article questions the sociological adequacy of the concept as conventionally deployed. Drawing on ethnographic work on the ways technological artefacts engage, and are engaged by, disabled bodies, we propose that the ‘affordances’ of technological objects are not reducible to their material constitution but are inextricably bound up with specific, historically situated modes of engagement and ways of life

    Targeting Class A and C Serine \u3b2-Lactamases with a Broad-Spectrum Boronic Acid Derivative

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    Production of \u3b2-lactamases (BLs) is the most widespread resistance mechanism adopted by bacteria to fight \u3b2-lactam antibiotics. The substrate spectrum of BLs has become increasingly broad, posing a serious health problem. Thus, there is an urgent need for novel BL inhibitors. Boronic acid transition-state analogues are able to reverse the resistance conferred by class A and C BLs. We describe a boronic acid analogue possessing interesting and potent broad-spectrum activity vs class A and C serine-based BLs. Starting from benzo(b)thiophene-2-boronic acid (BZBTH2B), a nanomolar non-\u3b2-lactam inhibitor of AmpC that can potentiate the activity of a third-generation cephalosporin against AmpC-producing resistant bacteria, we designed a novel broad-spectrum nanomolar inhibitor of class A and C BLs. Structure-based drug design (SBDD), synthesis, enzymology data, and X-ray crystallography results are discussed. We clarified the inhibitor binding geometry responsible for broad-spectrum activity vs serine-active BLs using double mutant thermodynamic cycle studies
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