Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.

Scleral matrix metalloproteinases, serine proteinase activity and hydrational capacity are increased in myopia induced by retinal image degradation

In the avian model of myopia, retinal image degradation quickly leads to ocular enlargement. We now give evidence that regionally specific changes in ocular size are correlated with both biomechanical indices of scleral remodeling, e.g. hydration capacity and with biochemical changes in proteinase activities. The latter include a 72 kDa matrix metalloproteinase (putatively MMP-2), other gelatin-binding MMPs, an acid pH MMP and a serine protease. Specifically, we have found that increases in scleral hydrational capacity parallel increases in collagen degrading activities. Gelatin zymography reveals that eyes with 7 days of retinal image degradation have elevated levels (1.4-fold) of gelatinolytic activities at 72 and 67 kDa M(r) in equatorial and posterior pole regions of the sclera while, after 14 days of treatment, increases are no longer apparent. Lower M(r) zymographic activities at 50, 46 and 37 kDa M(r) are collectively increased in eyes treated for both 7 and 14 days (1.4- and 2.4-fold respectively) in the equator and posterior pole areas of enlarging eyes. Western blot analyses of scleral extracts with an antibody to human MMP-2 reveals immunoreactive bands at 65, 30 and 25 kDa. Zymograms incubated under slightly acidic conditions reveal that, in enlarging eyes, MMP activities at 25 and 28 kDa M(r) are increased in scleral equator and posterior pole (1.6- and 4.5-fold respectively). A TIMP-like protein is also identified in sclera and cornea by Western blot analysis. Finally, retinal-image degradation also increases (~2.6-fold) the activity of a 23.5 kDa serine proteinase in limbus, equator and posterior pole sclera that is inhibited by aprotinin and soybean trypsin inhibitor. Taken together, these results indicate that eye growth induced by retinal-image degradation involves increases in the activities of multiple scleral proteinases that could modify the biomechanical properties of scleral structural components and contribute to tissue remodeling and growth.

University of Glasgow at ImageCLEFPhoto 2009 : optimising similarity and diversity in image retrieval

In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

Confronting the ‘resource curse or cure’ binary

The use of the curse or cure dichotomy to frame a discussion around the impacts of mining is an oversimplification, not least in the emphasis on one or the other (as opposed to curse and cure). It is, however, a potent trope for engaging critically with the consequences of mining not only in narrow economic terms but also in regard to political, social and environmental costs and benefits. Further, as Goodman and Worth (2008: 201) point out, to engage with the resource curse or cure question is to also engage more broadly with “the internal contradictions of capitalist development” as evident, for example, in divisions “between those who benefit from and those who bear the costs of accumulation” and the many conflicts—political, social, economic, environmental—attending resource extraction. It is in this sense that this volume mobilises the ‘resource curse or cure?’ motif.

A comparison of spatially explicit landscape representation methods and their relationship to stream condition

1. Biodiversity, water quality and ecosystem processes in streams are known to be influenced by the terrestrial landscape over a range of spatial and temporal scales. Lumped attributes (i.e. per cent land use) are often used to characterise the condition of the catchment; however, they are not spatially explicit and do not account for the disproportionate influence of land located near the stream or connected by overland flow. 2. We compared seven landscape representation metrics to determine whether accounting for the spatial proximity and hydrological effects of land use can be used to account for additional variability in indicators of stream ecosystem health. The landscape metrics included the following: a lumped metric, four inverse-distance-weighted (IDW) metrics based on distance to the stream or survey site and two modified IDW metrics that also accounted for the level of hydrologic activity (HA-IDW). Ecosystem health data were obtained from the Ecological Health Monitoring Programme in Southeast Queensland, Australia and included measures of fish, invertebrates, physicochemistry and nutrients collected during two seasons over 4 years. Linear models were fitted to the stream indicators and landscape metrics, by season, and compared using an information-theoretic approach. 3. Although no single metric was most suitable for modelling all stream indicators, lumped metrics rarely performed as well as other metric types. Metrics based on proximity to the stream (IDW and HA-IDW) were more suitable for modelling fish indicators, while the HA-IDW metric based on proximity to the survey site generally outperformed others for invertebrates, irrespective of season. There was consistent support for metrics based on proximity to the survey site (IDW or HA-IDW) for all physicochemical indicators during the dry season, while a HA-IDW metric based on proximity to the stream was suitable for five of the six physicochemical indicators in the post-wet season. Only one nutrient indicator was tested and results showed that catchment area had a significant effect on the relationship between land use metrics and algal stable isotope ratios in both seasons. 4. Spatially explicit methods of landscape representation can clearly improve the predictive ability of many empirical models currently used to study the relationship between landscape, habitat and stream condition. A comparison of different metrics may provide clues about causal pathways and mechanistic processes behind correlative relationships and could be used to target restoration efforts strategically.

Enhanced coloration efficiency for electrochromic devices based on anodized N2O5 / Electrodeposited MoO3 Binary Systems

There is a continuous quest for developing electrochromic (EC)transition metal oxides (TMOs) with increased coloration efficiency. As emerging TMOs, Nb2O5 films, even those of ordered anodized nanochannels, have failed to produce the required EC performance for practical applications. This is attributed to limitations presented by its relatively wide bandgap and low capacity for accommodating ions. To overcome such issues, MoO3 was electrodeposited onto Nb2O5 nanochannelled films as homogeneously conformal and stratified α-MoO3 coatings of different thickness. The EC performance of the resultant MoO3 coated Nb2O5 binary system was evaluated. The system exhibited a coloration efficiency of 149.0 cm2 C−1, exceeding that of any previous reports on MoO3 and Nb2O5 individually or their compounds. The enhancement was ascribed to a combination of the reduced effective bandgap of the binary system, the increased intercalation probability from the layered α-MoO3 coating, and a high surface-tovolume ratio, while the Nb2O5 nanochannelled templates provided stability and low impurity pathways for charge transfer to occur.

Integrating object locations in the memory representation of a spatial layout

The present study investigated how object locations learned separately are integrated and represented as a single spatial layout in memory. Two experiments were conducted in which participants learned a room-sized spatial layout that was divided into two sets of five objects. Results suggested that integration across sets was performed efficiently when it was done during initial encoding of the environment but entailed cost in accuracy when it was attempted at the time of memory retrieval. These findings suggest that, once formed, spatial representations in memory generally remain independent and integrating them into a single representation requires additional cognitive processes.

Control of core-shell structure and elemental composition of binary quantum dots

The possibility of initial stage control of the elemental composition and core/shell structure of binary SiC quantum dots by optimizing temporal variation of Si and C incoming fluxes and surface temperatures is shown via hybrid numerical simulations. Higher temperatures and influxes encourage the formation of a stoichiometric outer shell over a small carbon-enriched core, whereas lower temperatures result in a larger carbon-enriched core, Si-enriched undershell, and then a stoichiometric SiC outer shell. This approach is generic and is applicable to a broad range of semiconductor materials and nanofabrication techniques. © 2007 American Institute of Physics.

The path to stoichiometric composition of III–V binary quantum dots through plasma/ion-assisted self-assembly

Semiconductor III-V quantum dots (QDs) are particularly enticing components for the integration of optically promising III-V materials with the silicon technology prevalent in the microelectronics industry. However, defects due to deviations from a stoichiometric composition [group III: group V = 1] may lead to impaired device performance. This paper investigates the initial stages of formation of InSb and GaAs QDs on Si(1 0 0) through hybrid numerical simulations. Three situations are considered: a neutral gas environment (NG), and two ionized gas environments, namely a localized ion source (LIS) and a background plasma (BP) case. It is shown that when the growth is conducted in an ionized gas environment, a stoichiometric composition may be obtained earlier in the QD as compared to a NG. Moreover, the stoichiometrization time, tst, is shorter for the BP case compared to the LIS scenario. A discussion of the effect of ion/plasma-based tools as well as a range of process conditions on the final island size distribution is also included. Our results suggest a way to obtain a deterministic level of control over nanostructure properties (in particular, elemental composition and size) during the initial stages of growth which is a crucial step towards achieving highly tailored QDs suitable for implementation in advanced technological devices.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Looking beyond image and tourism : the role of flagship cultural projects in local arts development

State and local governments frequently look to flagship cultural projects to improve the city image and catalyze tourism but, in the process, often overlook their potential to foster local arts development. To better understand this role, the article examines if and how cultural institutions in Los Angeles and San Francisco attract and support arts-related activity. The analysis reveals that cultural flagships have mixed success in generating arts-based development and that their ability may be improved through attention to the local context, facility and institutional characteristics, and the approach of the sponsoring agencies. Such knowledge is useful for planners to enhance their revitalization efforts, particularly as the economic development potential of arts organizations and artists has become more apparent.