978 resultados para Active Vision
Resumo:
The OECD (2006 Starting Strong II: Early Childhood Education and Care. OECD Publishing: Paris) envisions early childhood education and care settings as meeting places for diverse social groups; places that build social capital. This vision was assessed in a comparison of three preschools types: full-fee paying, subsidised-fee and publicly funded. The social composition within each was examined and the connectedness of the children (n = 472) who attended compared. Publicly funded preschools had more socially diverse populations. The quantity of social connectedness did not differ but children in publicly funded preschools described higher quality social relationships. Not all preschool settings are socially diverse but, where they are, the quality of relationships is highest.
Resumo:
Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.
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This paper presents background of our research and result of our pilot study to find methods for convincing building users to become active building participants. We speculate this is possible by allowing and motivating users to customise and manage their own built environments. The ultimate aim of this research is to develop open, flexible and adaptive systems that bring awareness to building users to the extent they recognise spaces are for them to change rather than accept spaces are fixed and they are the ones to adapt. We argue this is possible if the architectural hardware is designed to adapt to begin with and more importantly if there are appropriate user interfaces that are designed to work with the hardware. A series of simple prototypes were made to study possibilities through making, installing and experiencing them. Ideas discussed during making and experiencing of prototypes were evaluated to generate further ideas. This method was very useful to speculate unexplored and unknown issues with respect to developing user interfaces for active buildings.
Resumo:
The use of adaptive wing/aerofoil designs is being considered, as they are promising techniques in aeronautic/ aerospace since they can reduce aircraft emissions and improve aerodynamic performance of manned or unmanned aircraft. This paper investigates the robust design and optimization for one type of adaptive techniques: active flow control bump at transonic flow conditions on a natural laminar flow aerofoil. The concept of using shock control bump is to control supersonic flow on the suction/pressure side of natural laminar flow aerofoil that leads to delaying shock occurrence (weakening its strength) or boundary layer separation. Such an active flow control technique reduces total drag at transonic speeds due to reduction of wave drag. The location of boundary-layer transition can influence the position and structure of the supersonic shock on the suction/pressure side of aerofoil. The boundarylayer transition position is considered as an uncertainty design parameter in aerodynamic design due to the many factors, such as surface contamination or surface erosion. This paper studies the shock-control-bump shape design optimization using robust evolutionary algorithms with uncertainty in boundary-layer transition locations. The optimization method is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing, and asynchronous evaluation. The use of adaptive wing/aerofoil designs is being considered, as they are promising techniques in aeronautic/ aerospace since they can reduce aircraft emissions and improve aerodynamic performance of manned or unmanned aircraft. This paper investigates the robust design and optimization for one type of adaptive techniques: active flow control bump at transonic flow conditions on a natural laminar flow aerofoil. The concept of using shock control bump is to control supersonic flow on the suction/pressure side of natural laminar flow aerofoil that leads to delaying shock occurrence (weakening its strength) or boundary-layer separation. Such an active flow control technique reduces total drag at transonic speeds due to reduction of wave drag. The location of boundary-layer transition can influence the position and structure of the supersonic shock on the suction/pressure side of aerofoil. The boundarylayer transition position is considered as an uncertainty design parameter in aerodynamic design due to the many factors, such as surface contamination or surface erosion. This paper studies the shock-control-bump shape design optimization using robust evolutionary algorithms with uncertainty in boundary-layer transition locations. The optimization method is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing, and asynchronous evaluation. Two test cases are conducted: the first test assumes the boundary-layer transition position is at 45% of chord from the leading edge, and the second test considers robust design optimization for the shock control bump at the variability of boundary-layer transition positions. The numerical result shows that the optimization method coupled to uncertainty design techniques produces Pareto optimal shock-control-bump shapes, which have low sensitivity and high aerodynamic performance while having significant total drag reduction.
Resumo:
The practice of robotics and computer vision each involve the application of computational algorithms to data. The research community has developed a very large body of algorithms but for a newcomer to the field this can be quite daunting. For more than 10 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This new book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes over 1000 MATLAB® and Simulink® examples and figures. The book is a real walk through the fundamentals of mobile robots, navigation, localization, arm-robot kinematics, dynamics and joint level control, then camera models, image processing, feature extraction and multi-view geometry, and finally bringing it all together with an extensive discussion of visual servo systems.
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Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.
Resumo:
The importance of mitogen-activated protein kinase signaling in melanoma is underscored by the prevalence of activating mutations in N-Ras and B-Raf, yet clinical development of inhibitors of this pathway has been largely ineffective, suggesting that alternative oncogenes may also promote melanoma. Notch is an interesting candidate that has only been correlated with melanoma development and progression; a thorough assessment of tumor-initiating effects of activated Notch on human melanocytes would clarify the mounting correlative evidence and perhaps identify a novel target for an otherwise untreatable disease. Analysis of a substantial panel of cell lines and patient lesions showed that Notch activity is significantly higher in melanomas than their nontransformed counterparts. The use of a constitutively active, truncated Notch transgene construct (N(IC)) was exploited to determine if Notch activation is a "driving" event in melanocytic transformation or instead a "passenger" event associated with melanoma progression. N(IC)-infected melanocytes displayed increased proliferative capacity and biological features more reminiscent of melanoma, such as dysregulated cell adhesion and migration. Gene expression analyses supported these observations and aided in the identification of MCAM, an adhesion molecule associated with acquisition of the malignant phenotype, as a direct target of Notch transactivation. N(IC)-positive melanocytes grew at clonal density, proliferated in limiting media conditions, and also exhibited anchorage-independent growth, suggesting that Notch alone is a transforming oncogene in human melanocytes, a phenomenon not previously described for any melanoma oncogene. This new information yields valuable insight into the basic epidemiology of melanoma and launches a realm of possibilities for drug intervention in this deadly disease.
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In this paper we describe a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system. It is capable of producing intricate three-dimensional maps over many kilometers and in real time. We consider issues concerning the intrinsic quality of the built maps and describe our progress towards adding semantic labels to maps via scene de-construction and labeling. We show how our choices of representation, inference methods and use of both topological and metric techniques naturally allow us to fuse maps built from multiple sessions with no need for manual frame alignment or data association.