920 resultados para Perceptual closure


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Prevailing video adaptation solutions change the quality of the video uniformly throughout the whole frame in the bitrate adjustment process; while region-of-interest (ROI)-based solutions selectively retains the quality in the areas of the frame where the viewers are more likely to pay more attention to. ROI-based coding can improve perceptual quality and viewer satisfaction while trading off some bandwidth. However, there has been no comprehensive study to measure the bitrate vs. perceptual quality trade-off so far. The paper proposes an ROI detection scheme for videos, which is characterized with low computational complexity and robustness, and measures the bitrate vs. quality trade-off for ROI-based encoding using a state-of-the-art H.264/AVC encoder to justify the viability of this type of encoding method. The results from the subjective quality test reveal that ROI-based encoding achieves a significant perceptual quality improvement over the encoding with uniform quality at the cost of slightly more bits. Based on the bitrate measurements and subjective quality assessments, the bitrate and the perceptual quality estimation models for non-scalable ROI-based video coding (AVC) are developed, which are found to be similar to the models for scalable video coding (SVC).

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Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

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Children’s literature has conventionally and historically been concerned with identity and the often tortuous journey to becoming a subject who is generally older and wiser, a journey typically characterised by mishap, adventure, and detours. Narrative closure in children’s and young adult novels and films typically provides a point of self-realisation or self-actualisation, whereby the struggles of finding one’s “true” identity have been overcome. In this familiar coming-of-age narrative, there is often an underlying premise of an essential self that will emerge or be uncovered. This kind of narrative resolution provides readers with a reassurance that things will work for the best in the end, which is an enduring feature of children’s literature, and part of liberal-humanism’s project of harmonious individuality. However, uncertainty is a constant that has always characterised the ways lives are lived, regardless of best-laid plans. Children’s literature provides a field of narrative knowledge whereby readers gain impressions of childhood and adolescence, or more specifically, knowledge of ways of being at a time in life, which is marked by uncertainty. Despite the prevalence of children’s texts which continue to offer normative ways of being, in particular, normative forms of gender behaviour, there are texts which resist the pull for characters to be “like everyone else” by exploring alternative subjectivities. Fiction, however, cannot be regarded as a source of evidence about the material realities of life, as its strength lies in its affective and imaginative dimensions, which nevertheless can offer readers moments of reflection, recognition, or, in some cases, reality lessons. As a form of cultural production, contemporary children’s literature is highly responsive to social change and political debates, and is crucially implicated in shaping the values, attitudes and behaviours of children and young people.

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There is currently little guidance in the Australian literature in relation to how to design an effective capstone experience. As a result, universities often fail to provide students with a genuine culminating experience in the final year of their degree. This paper will consider the key objectives of capstone experiences – closure and transition – and will examine how these objectives can be met by a work-integrated learning (WIL) experience. This paper presents an argument for the inclusion of WIL as a component of a capstone experience. WIL is consistent with capstone objectives in focusing on the transition to professional practice. However, the capacity of WIL to meet all of the objectives of capstones may be limited. The paper posits that while WIL should be considered as a potential component of a capstone experience, educators should ensure that WIL is not equated with a capstone experience unless it is carefully designed to ensure that all the objectives of capstones are met.

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This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.

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This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

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A whole tradition is said to be based on the hierarchical distinction between the perceptual and conceptual. In art, Niklas Luhmann argues, this schism is played out and repeated in conceptual art. This paper complicates this depiction by examining Ian Burn's last writings in which I argue the artist-writer reviews the challenge of minimal-conceptual art in terms of its perceptual pre-occupations. Burn revisits his own work and the legacy of minimal-conceptual by moving away from the kind of ideology critique he is best known for internationally in order to reassert the long overlooked visual-perceptual preoccupations of the conceptual in art.

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Skin plays a key role in protecting the body from the onslaught of pathogens and toxins we meet during our lifetime; thus, out of necessity, we have developed a rapid repair mechanism that quickly plugs any holes in this vital organ. Upon injury, a series of highly coordinated overlapping events, that include inflammatory, proliferation and maturation phases, result in the hasty closure of the wound and restoration of skin integrity. Over the past decade it has become clear that a number of immune cells that regulate the inflammatory phase, whilst important for removal of invading pathogens, are not necessary for repair and in fact may be responsible for the subsequent scar formation that seems to have resulted from having such a rapid repair process. The magnitude and length of inflammation in the wound not only appears to dictate the extent of scar formation but also in some cases may even prevent wound closure. In this review we will explore the two sides of inflammation in wound healing and review current and future drug therapies that target inflammation to modulate the healing outcome.

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Random walk models based on an exclusion process with contact effects are often used to represent collective migration where individual agents are affected by agent-to-agent adhesion. Traditional mean field representations of these processes take the form of a nonlinear diffusion equation which, for strong adhesion, does not predict the averaged discrete behavior. We propose an alternative suite of mean-field representations, showing that collective migration with strong adhesion can be accurately represented using a moment closure approach.

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This submission is directed to addressing Issue 4 only – Entering a village and closure – implications for residents; and one question only – What particular items do you consider should be particularly addressed as part of the disclosure requirements for prospective retirement village residents? The recommendations below are premised on the basis that information to enable informed choice needs to be clearly presented, easy to understand and, while legal advice and assistance remains essential for any form of ‘conveyancing’ process, should enable decision making by prospective residents independent of that legal advice.

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Flightless (Flii) is upregulated in response to wounding and has been shown to function in wound closure and scarring. In macrophages intracellular Flii negatively modulates TLR signalling and dampens cytokine production. We now show that Flii is constitutively secreted from macrophages and fibroblasts and is present in human plasma. Secretion from fibroblasts is upregulated in response to scratch wounding and LPS-activated macrophages also temporally upregulate their secretion of Flii. Using siRNA, wild-type and mutant proteins we show that Flii is secreted via a late endosomal/lysosomal pathway that is regulated by Rab7 and Stx11. Flii contains 11 leucine rich repeat (LRR) domains in its N-terminus that have nearly 50% similarity to those in the extracellular pathogen binding portion of Toll-like receptor 4 (TLR4). We show secreted Flii can also bind LPS and has the ability to alter macrophage activation. LPS activation of macrophages in Flii depleted conditioned media leads to enhanced macrophage activation and increased TNF secretion compared to cells activated in the presence of Flii. These results show secreted Flii binds to LPS and in doing so alters macrophage activation and cytokine secretion, suggesting that like the intracellular pool of Flii, secreted Flii also has the ability to alter inflammation.

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Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearance-based localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

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Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

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Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

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Conducting research into crime and criminal justice carries unique challenges. This Handbook focuses on the application of 'methods' to address the core substantive questions that currently motivate contemporary criminological research. It maps a canon of methods that are more elaborated than in most other fields of social science, and the intellectual terrain of research problems with which criminologists are routinely confronted. Drawing on exemplary studies, chapters in each section illustrate the techniques (qualitative and quantitative) that are commonly applied in empirical studies, as well as the logic of criminological enquiry. Organized into five sections, each prefaced by an editorial introduction, the Handbook covers: • Crime and Criminals • Contextualizing Crimes in Space and Time: Networks, Communities and Culture • Perceptual Dimensions of Crime • Criminal Justice Systems: Organizations and Institutions • Preventing Crime and Improving Justice Edited by leaders in the field of criminological research, and with contributions from internationally renowned experts, The SAGE Handbook of Criminological Research Methods is set to become the definitive resource for postgraduates, researchers and academics in criminology, criminal justice, policing, law, and sociology.