Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

An exploration of feature detector performance in the thermal-infrared modality

Thermal-infrared images have superior statistical properties compared with visible-spectrum images in many low-light or no-light scenarios. However, a detailed understanding of feature detector performance in the thermal modality lags behind that of the visible modality. To address this, the first comprehensive study on feature detector performance on thermal-infrared images is conducted. A dataset is presented which explores a total of ten different environments with a range of statistical properties. An investigation is conducted into the effects of several digital and physical image transformations on detector repeatability in these environments. The effect of non-uniformity noise, unique to the thermal modality, is analyzed. The accumulation of sensor non-uniformities beyond the minimum possible level was found to have only a small negative effect. A limiting of feature counts was found to improve the repeatability performance of several detectors. Most other image transformations had predictable effects on feature stability. The best-performing detector varied considerably depending on the nature of the scene and the test.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

What do we currently know about designing and evaluating road safety advertising?

Overview: What we currently know - content design and evaluation The direct role (persuasive effects) of advertising Review of some key findings within a conceptual framework of the persuasive process Definitional inconsistencies, methodological limitations, & gaps in existing knowledge Suggested issues/directions for future advertising research

Feature-domain super-resolution framework for gabor-based face and iris recognition

The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

Robust facial feature extraction and matching

Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.

We just make the pictures…?’ How work is portrayed in children’s feature length films

This article explores how adult paid work is portrayed in 'family' feature length films. The study extends previous critical media literature which has overwhelmingly focused on depictions of gender and violence, exploring the visual content of films that is relevant to adult employment. Forty-two G/PG films were analyzed for relevant themes. Consistent with the exploratory nature of the research, themes emerged inductively from the films' content. Results reveal six major themes: males are more visible in adult work roles than women; the division of labour remains gendered; work and home are not mutually exclusive domains; organizational authority and power is wielded in punitive ways; there are avenues to better employment prospects; and status/money is paramount. The findings of the study reflect a range of subject matters related to occupational characteristics and work-related communication and interactions which are typically viewed by children in contemporary society.

Strategic aesthetics in advertising campaigns : implications for art direction education

For over half a century art directors within the advertising industry have been adapting to the changes occurring in media, culture and the corporate sector, toward enhancing professional performance and competitiveness. These professionals seldom offer explicit justification about the role images play in effective communication. It is uncertain how this situation affects advertising performance, because advertising has, nevertheless, evolved in parallel to this as an industry able to fabricate new opportunities for itself. However, uncertainties in the formalization of art direction knowledge restrict the possibilities of knowledge transfer in higher education. The theoretical knowledge supporting advertising art direction has been adapted spontaneously from disciplines that rarely focus on specific aspects related to the production of advertising content, like, for example: marketing communication, design, visual communication, or visual art. Meanwhile, in scholarly research, vast empirical knowledge has been generated about advertising images, but often with limited insight into production expertise. Because art direction is understood as an industry practice and not as an academic discipline, an art direction perspective in scholarly contributions is rare. Scholarly research that is relevant to art direction seldom offers viewpoints to help understand how it is that research outputs may specifically contribute to art direction practices. This thesis is dedicated to formally understanding the knowledge underlying art direction and using it to explore models for visual analysis and knowledge transfer in higher education. The first three chapters of this thesis offer, firstly, a review of practical and contextual aspects that help define art direction, as a profession and as a component in higher education; secondly, a discussion about visual knowledge; and thirdly, a literature review of theoretical and analytic aspects relevant to art direction knowledge. Drawing on these three chapters, this thesis establishes explicit structures to help in the development of an art direction curriculum in higher education programs. Following these chapters, this thesis explores a theoretical combination of the terms ‘aesthetics’ and ‘strategy’ as foundational notions for the study of art direction. The theoretical exploration of the term ‘strategic aesthetics’ unveils the potential for furthering knowledge in visual commercial practices in general. The empirical part of this research explores ways in which strategic aesthetics notions can extend to methodologies of visual analysis. Using a combination of content analysis and of structures of interpretive analysis offered in visual anthropology, this research discusses issues of methodological appropriation as it shifts aspects of conventional methodologies to take into consideration paradigms of research that are producer-centred. Sampled out of 2759 still ads from the online databases of Cannes Lions Festival, this study uses an instrumental case study of love-related advertising to facilitate the analysis of content. This part of the research helps understand the limitations and functionality of the theoretical and methodological framework explored in the thesis. In light of the findings and discussions produced throughout the thesis, this project aims to provide directions for higher education in relation to art direction and highlights potential pathways for further investigation of strategic aesthetics.

Just give me the facts? literalism versus symbolism in B2B advertising

For decades the prevailing idea in B2B marketing has been that buyers are motivated by product/service specifications. Sellers are put on approved supplier lists, invited to respond to RFPs, and are selected on the basis of superior products, at the right price, delivered on time. The history of B2B advertising is filled with the advice “provide product specifications” and your advertising will be noticed, lead to sales inquiries, and eventually result in higher sales. Advertising filled with abstractions might work in the B2C market, but the B2B marketplace is about being literal. What we know about advertising — and particularly the message component of advertising — is based on a combination of experience, unproven ideas and a bit of social science. Over the years, advertising guidelines produced by the predecessors of BMA (National Industrial Advertising Association, Association of Industrial Advertising, and the Business/Professional Advertising Association) stressed emphasizing product features and tangible benefits. The major publishers of B2B magazines, e.g., McGraw-Hill, Penton Publishing, et al. had similar recommendations. Also, B2B marketing books recommend advertising that focuses on specific product features (Kotler and Pfoertsch, 2006; Lamons, 2005). In more recent times, abstraction in advertising messages has penetrated the B2B marketplace. Even though such advertising legends as David Ogilvy (1963, 1985) frequently recommended advertising based on hard-core information, we’ve seen the growing use of emotional appeals, including humor, fear, parental affection, etc. Beyond the use of emotion, marketers attempt to build a stronger connection between their brands and buyers through the use of abstraction and symbolism. Below are two examples of B2B advertisements — Figure 1A is high in literalism and Figure 1B is high in symbolism. Which approach — a “left-brain” (literal) or “right brain” (symbolic) is more effective in B2B advertising? Are the advertising message creation guidelines from the history of B2B advertising accurate? Are the foundations of B2B message creation (experience and unproven ideas) sound?

Can we teach advertising students to think? Strategies to engage student thinking

Understanding and effectively managing students’ engagement in education plays a significant role in enhancing learning processes and outcomes. Research has shown that students learn more when they are actively engaged in their learning. However, as many educators know, this is not as easy as one might expect. Using a range of teaching approaches, we attempt to impart knowledge and develop understanding and comprehension (Angelo 1993; Biggs and Telfer 1987; Patti 2003; Ranburuth and McCormick 2001). These vary from “information dump” or teacher-centric approaches, to those that stimulate more active involvement. From the literature, we know that experiential learning, such as those strategies that help students acquire practice skills, apply critical thought and active learning, are likely to have achieve higher levels of intellectual skill and ability (Benson and Blackman 2003; Hampton and Lawrence 1995; Hopkinson and Hogg 2004; Kolb 1984).

The role of alternative message strategies in advertising performance : challenges to the B2B marketing paradigm

In this study the impact of message strategy on advertising performance will be in examined in a business-to-business (B2B) context. From a theoretical standpoint, the study will explore differences in message type between symbolic and literal approaches in B2B advertisements. While there has been much discussion on the effect of symbolism, (eg. metaphors, abstract images and figurative language), an empirically-tested scale that measures the degree of symbolism has not been developed. This research project focuses on development of a methodological scale to accurately test the difference in the direction of message appeals. Thus, insights in the role of message strategy in the B2B adoption process are anticipated with contributions in future consumer and business advertising research.

Buy, boycott or blog : exploring online consumer power to share, discuss and distribute controversial advertising messages

The availability of new media as a universal communication tool has an impact on the power of the general public to comment on a variety of issues. This paper examines this increase in consumer power with respect to bloggers. The research context is controversial advertising, and specifically Tourism Australia’s “Where the bloody hell are you?” campaign. By utilising Denegri-Knott’s (2006) four on-line power strategies, a content analysis of weblogs reveals that consumers are distributing information, opinion and even banned advertising material, thereby forming power hubs of like-minded people, with the potential to become online pressure groups. The consequences and implications of this augmented power on regulators, advertisers and bloggers are explored. The findings contribute to the understanding of blogs as a new communication platform and bloggers as a new demographic of activists in the process of advertising.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.