Automatic Image Annotation Based on Particle Swarm Optimization and Support Vector Clustering

With the progress of network technology, there are more and more digital images of the internet. But most images are not semantically marked, which makes it difficult to retrieve and use. In this paper, a new algorithm is proposed to automatically annotate images based on particle swarm optimization (PSO) and support vector clustering (SVC). The algorithm includes two stages: firstly, PSO algorithm is used to optimize SVC; secondly, the trained SVC algorithm is used to annotate the image automatically. In the experiment, three datasets are used to evaluate the algorithm, and the results show the effectiveness of the algorithm

Automatic semantic and geometric enrichment of CityGML building models using HoG-based template matching

Semantically rich 3D building models give the potential for a wealth of rich geo-spatially-enabled applications such as cultural heritage augmented reality, urban planning, radio network planning and personal navigation. However, the majority of existing building models lack much if any semantic detail. This work demonstrates a novel method for automatically locating subclasses of windows and doors, using computer vision techniques including the histogram of oriented gradient (HoG) template matching, and automatically creating enriched CityGML content for the matched windows and doors. Good results were achieved for class identification with potential for further refinement of subclasses of windows and doors and other architectural features. It is part of a wider project to bring even richer semantic content to 3D geo-spatial building models

Automatic semantic and geometric enrichment of CityGML 3D building models of varying architectural styles with HOG-based template matching

While the number of 3D geo-spatial digital models of buildings with cultural heritage interest is burgeoning, most lack semantic annotation that could be used to inform users of mobile and desktop applications about the architectural features and origins of the buildings. Additionally, while automated reconstruction of 3D building models is an active research area, the labelling of architectural features (objects) is comparatively less well researched, while distinguishing between different architectural styles is less well researched still. Meanwhile, the successful automatic identification of architectural objects, typified by a comparatively less symmetrical or less regular distribution of objects on façades, particularly on older buildings, has so far eluded researchers. This research has addressed these issues by automating the semantic and geometric enrichment of existing 3D building models by using Histogram of Oriented Gradients (HOG)-based template matching. The methods are applied to the texture maps of 3D building models of 20th century styles, of Georgian-Regency (1715-1830) style and of the Norman (1066 to late 12th century) style, where the amalgam of styles present on buildings of the latter style necessitates detection of styles of the Gothic tradition (late 12th century to present day). The most successful results were obtained when applying a set of heuristics including the use of real world dimensions, while a Support Vector Machine (SVM)-based machine learning approach was found effective in obviating the need for thresholds on matchscores when making detection decisions

The cognitive antecedents of psychosis-like (anomalous) experiences: variance within a stratified quota sample of the general population

In the general population, psychosis-like experiences have been extensively studied under the psychometric rubric of schizotypy (psychosis-proneness). As such, Phase 1 of this thesis aimed to assess the distribution of schizotypal traits and associated personality correlates displayed within a quota sample of the general population stratified by Gender and Ageband, the emphasis being upon anomalous experiences (positive schizotypy). Respondents (N = 130) completed a battery of established self-report measures assessing thirteen areas of personal experience. Correlational analysis revealed that eleven of the measures of ostensibly anomalous experiences possessed significant intercorrelations. Subsequent principal components analysis identified three factors accounting for 64.91% of the total variance; the factor accounting for the greatest proportion of variance (42.97%) was interpreted as representing a psychological disposition towards reporting ‘Anomalous Cognitions’. The other two factors are named ‘Lifeview System’ (12.60% of total variance) and ‘Social Adaptation Skills’ (9.34% of total variance). From the principal factor inclusion criteria for Phase 2 of the research are explicated. No significant mean Gender differences were revealed for the six self-report measures that provided unique contributions toward anomalous cognitions, the two self-report measures that uniquely contributed toward a lifeview system, or for the single self-report measure that uniquely contributed toward social adaptation skills. Additionally, four of the nine self-report measures which provided unique factorial contributions generated significant mean differences between Agebands, with a further three providing trends toward significant mean differences. Implications for the role of anomalous cognitions, a framework for a lifeview system, and social adaptation skills with regard to psychosis-proneness are discussed. From the primary factor (anomalous cognitions), three experimental groups were identified for cognitive testing: respondents scoring 1) ≤ 20th percentile; 2) 10% ± the mean; and 3) ≥ 80th percentile. This procedure provided a total of 78 participants (three x 26) for Phase 2 testing. Phase 2 of this thesis sought to identify some of the cognitive mechanisms underpinning subclinical anomalous cognitions with a view to deciphering which measures best predicted experimental group membership. A comprehensive literature review highlighted six domains of cognition, five accompanying self-report measures, and two measures of intelligence functioning (verbal and fluid/visuoconstructive), which, following previous research, were utilised as covariate measures. Based on prescribed delineation points, participants were allocated, according to scores on the primary factor from Phase 1, to one of three experimental groups (low-, mid, and high-anomalous cognitions). Of the six cognitive domains—1) sustained visual attention; 2) false (illusory) memory; 3) probability reasoning (decision making); 4) object recognition; 5) reality monitoring; and 6) self-monitoring—four succeeded in eliciting significant mean differences between experimental groups with the noted exceptions of sustained visual attention and self-monitoring. Subsequent canonical discriminant analyses identified that the best predictors of XPG membership were the number of critical lures recognised on the false memory test, the number of correct responses and confidence when uncertain on the object recognition test, plus two self-report measures pertaining to comorbid psychopathology and the vividness of visual imagery. In light of previous research, the inclusion of fasle (illusory) memory biases, the comorbidity of mental pathology (especially, depressive and anxiety-related symptoms), and the vividness of visual imagery are unsurprising; however, the two object recognition variables (the ‘number of correct responses’ and ‘confidence when uncertain’) offer exciting avenues for future research into the continuum of psychosis. Moreover, the ‘confidence when uncertain’ data from the object recognition test (perceptual) and the probability reasoning (decision making) data from the Beads test suggest that cognitive underconfidence may well be an enduring personality disposition in those reporting elevated levels of anomalous cognitions, including positive and disorganised schizotypal personality traits. The results of Phase 2 add confirmatory evidence to previous research suggestive of memory and perceptual biases plus comorbid psychopathology and the vividness of visual imagery as being integral to the psychogenesis of psychosis-like (anomalous) symptomatology