411 resultados para image classification


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Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency.

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Since the first destination image studies were published in the early 1970s, the field has become one of the most popular in the tourism literature. While reviews of the destination image literature show no commonly agreed conceptualisation of the construct, researchers have predominantly used structured questionnaires for measurement. There has been criticism that the way some of these scales have been selected means a greater likelihood of attributes being irrelevant to participants. This opens up the risk of stimulating uninformed responses. The issue of uninformed response was first raised as a source of error 60 years ago. However, there has been little, if any, discussion in relation to destination image measurement, studies of which often require participants to provide opinion-driven rather than fact-based responses. This paper reports the trial of a ‘don’t know’ (DK) non-response option for participants in two destination image questionnaires. It is suggested the use of a DK option provides participants with an alternative to i) skipping the question, ii) using the scale midpoint to denote neutrality, or iii) providing an uninformed response. High levels of DK usage by participants can then alert the marketer of the need to improve awareness of destination performance for potential salient attributes.

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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.

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The rank and census are two filters based on order statistics which have been applied to the image matching problem for stereo pairs. Advantages of these filters include their robustness to radiometric distortion and small amounts of random noise, and their amenability to hardware implementation. In this paper, a new matching algorithm is presented, which provides an overall framework for matching, and is used to compare the rank and census techniques with standard matching metrics. The algorithm was tested using both real stereo pairs and a synthetic pair with ground truth. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

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Bridges are currently rated individually for maintenance and repair action according to the structural conditions of their elements. Dealing with thousands of bridges and the many factors that cause deterioration, makes this rating process extremely complicated. The current simplified but practical methods are not accurate enough. On the other hand, the sophisticated, more accurate methods are only used for a single or particular bridge type. It is therefore necessary to develop a practical and accurate rating system for a network of bridges. The first most important step in achieving this aim is to classify bridges based on the differences in nature and the unique characteristics of the critical factors and the relationship between them, for a network of bridges. Critical factors and vulnerable elements will be identified and placed in different categories. This classification method will be used to develop a new practical rating method for a network of railway bridges based on criticality and vulnerability analysis. This rating system will be more accurate and economical as well as improve the safety and serviceability of railway bridges.

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Greater than 750 individual particles have now been selected from collection flags housed in the JSC Cosmic Dust Curatorial Facility and most have been documented in the Cosmic Dust Catalogs [1]. As increasing numbers of particles are placed in Cosmic Dust Collections, and a greater diversity of particles are introduced to the stratosphere through natural and man-made processes (e.g. decaying orbits of space debris [2]), there is an even greater need for a classification scheme to encompass all stratospheric particles rather than only extraterrestrial particles. The fundamental requirements for a suitable classification scheme have been outlined in earlier communications [3,4]. A quantitative survey of particles on collection flag W7017 indicates that there is some bias in the number of samples selected within a given category for the Cosmic Dust Catalog [5]. However, the sample diversity within this selection is still appropriate for the development of a reliable classification scheme. In this paper, we extend the earlier works on stratospheric particle classification to include particles collected during the period May 1981 to November 1983.

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We applied a texture-based flow visualisation technique to a numerical hydrodynamic model of the Pumicestone Passage in southeast Queensland, Australia. The quality of the visualisations using our flow visualisation tool, are compared with animations generated using more traditional drogue release plot and velocity contour and vector techniques. The texture-based method is found to be far more effective in visualising advective flow within the model domain. In some instances, it also makes it easier for the researcher to identify specific hydrodynamic features within the complex flow regimes of this shallow tidal barrier estuary as compared with the direct and geometric based methods.

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Concern that poor image of UK construction industry is restricting recruitment has lead to call for action. This paper gives the results of a recent comparative analysis of the image of both UK and Hungarian industries which indicates the UK image to be relatively good. The perceived cause of Hungarian problems is the poor level of organisation and management.

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This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

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Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

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We introduce a new image-based visual navigation algorithm that allows the Cartesian velocity of a robot to be defined with respect to a set of visually observed features corresponding to previously unseen and unmapped world points. The technique is well suited to mobile robot tasks such as moving along a road or flying over the ground. We describe the algorithm in general form and present detailed simulation results for an aerial robot scenario using a spherical camera and a wide angle perspective camera, and present experimental results for a mobile ground robot.

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Health care interventions in the area of body image disturbance and eating disorders largely involve individual treatment approaches, while prevention and health promotion are relatively underexplored. A review of health promotion activities in the area of body image in Australia revealed three programmes, the most extensive and longest standing having been established in 1992. The aims of this programme are to reduce body image dissatisfaction and inappropriate eating behaviour, especially among women. Because health promotion is concerned with the social aspects of health, it was hypothesized by the authors that a social understanding of body image and eating disorders might be advanced in a health promotion setting and reflected in the approach to practice. In order to examine approaches to body image in health promotion, 10 health professionals responsible for the design and management of this programme participated in a series of semi-structured interviews between 1997 and 2000. Three discursive themes were evident in health workers' explanations of body image problems: (1) cognitive-behavioural themes; (2) gender themes; and (3) socio-cultural themes. While body image problems were constructed as psychological problems that are particularly experienced by women, their origins were largely conceived to be socio-cultural. The implications of these constructions are critically discussed in terms of the approach to health promotion used in this programme.

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This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

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This practice-based presentation explores the role of fashion as an agent for social inclusion and ethical design practice in communities. The Stitchery Collective is an artist-run initiative based in Brisbane, Australia. Operating at the intersection of craft and design, the fashion-based initiative challenges the assumption that fashion is designed, produced and consumed exclusively in the commercial sector. As a not-for-profit cooperative, the stitchery collective is the first and only fashion organisation in Australia to attract funding under the national and state artist-run-initiative scheme. The collective approach extends to the stitchery design practice, facilitated by individual practitioners working within the organisation who devise programs in the context of collaborative and socially engaged design. Working under the banner of a question, Can fashion be more than pretty clothes for pretty people? the stitchery works to extend the cultural field of fashion practice in the 21st century. The premise of dress as a ‘significant creative or cultural expression’ has informed the expanded definition of fashion practice, as adopted by the stitchery. This alternative classification has fostered partnerships with numerous community groups, including those marginalised in the contemporary fashion context such as recent migrants and refugees. Community engagement programs span design, sewing and up-cycling workshops, sustainability lectures, clothing swaps and public education seminars, supported by partnerships with various cultural, government and educational institutions. In 2011, the stitchery travelled to the Venice Biennale’s 3rd International Children’s Carnival, hosting a workshop series and installation to promote design for sustainability. The proven potential for design to connect community members has motivated the stitchery to question the opportunity for fashion practice to, perhaps uncharacteristically, operate under the banner of ‘design for social good’. Acknowledging craft and design as relational fields, this presentation expands fashion as a tool for social innovation and sustainable practice. The stitchery dislocates the consumer status of fashion with small-scale, localised projects; moving beyond fashion as a dictum of social class to an alternative model that is accessible, conscious, flexible, connected and sustainable. As an undefined post-industrial future approaches, the non-commercial status of the stitchery practice might work to present an image of the active post-consumer. How can the stitchery propose a resilient model of design for the future?