Towards condition-invariant sequence-based route recognition

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 mountainbiking 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.

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

Acoustic component detection for automatic species recognition in environmental monitoring

Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

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.

Professional growth through working together : a study of reciprocal benefits for teacher and education advisor through classroom based professional development

Teacher professional development provided by education advisors as one-off, centrally offered sessions does not always result in change in teacher knowledge, beliefs, attitudes or practice in the classroom. As the mathematics education advisor in this study, I set out to investigate a particular method of professional development so as to influence change in a practising classroom teacher’s knowledge and practices. The particular method of professional development utilised in this study was based on several principles of effective teacher professional development and saw me working regularly in a classroom with the classroom teacher as well as providing ongoing support for her for a full school year. The intention was to document the effects of this particular method of professional development in terms of the classroom teacher’s and my professional growth to provide insights for others working as education advisors. The professional development for the classroom teacher consisted of two components. The first was the co-operative development and implementation of a mental computation instructional program for the Year 3 class. The second component was the provision of ongoing support for the classroom teacher by the education advisor. The design of the professional development and the mental computation instructional program were progressively refined throughout the year. The education advisor fulfilled multiple roles in the study as teacher in the classroom, teacher educator working with the classroom teacher and researcher. Examples of the professional growth of the classroom teacher and the education advisor which occurred as sequences of changes (growth networks, Hollingsworth, 1999) in the domains of the professional world of the classroom teacher and education advisor were drawn from the large body of data collected through regular face-to-face and email communications between the classroom teacher and the education advisor as well as from transcripts of a structured interview. The Interconnected Model of Professional Growth (Clarke & Hollingsworth, 2002; Hollingsworth, 1999) was used to summarise and represent each example of the classroom teacher’s professional growth. A modified version of this model was used to summarise and represent the professional growth of the education advisor. This study confirmed that the method of professional development utilised could lead to significant teacher professional growth related directly to her work in the classroom. Using the Interconnected Model of Professional Growth to summarise and represent the classroom teacher’s professional growth and the modified version for my professional growth assisted with the recognition of examples of how we both changed. This model has potential to be used more widely by education advisors when preparing, implementing, evaluating and following-up on planned teacher professional development activities. The mental computation instructional program developed and trialled in the study was shown to be a successful way of sequencing and managing the teaching of mental computation strategies and related number sense understandings to Year 3 students. This study was conducted in one classroom, with one teacher in one school. The strength of this study was the depth of teacher support provided made possible by the particular method of the professional development, and the depth of analysis of the process. In another school, or with another teacher, this might not have been as successful. While I set out to change my practice as an education advisor I did not expect the depth of learning I experienced in terms of my knowledge, beliefs, attitudes and practices as an educator of teachers. This study has changed the way in which I plan to work as an education advisor in the future.

Developing and enhancing independent learning skills : using video tutorials as a means of helping students help themselves

Purpose – The purpose of this paper is to examine the use of short video tutorials in a post-graduate accounting subject, as a means of helping students develop and enhance independent learning skills. Design/methodology/approach – In total, five short (approximately five to 10 minutes) video tutorials were introduced in an effort to shift the reliance for learning from the lecturer to the student. Data on students’ usage of online video tutorials, and comments by students in university questionnaires were collated over three semesters from 2008 to 2009. Interviews with students were then conducted in late 2009 to more comprehensively evaluate the use and perceived benefits of video tutorials. Findings – Findings reveal preliminary but positive outcomes in terms of both more efficient and effective teaching and learning. Research limitations/implications – The shift towards more independent learning through the use of video tutorials has positive implications for educators, employers, and professional accounting bodies; each of whom has identified the need for this skill in accounting graduates. Practical implications – The use of video tutorials has the potential for more rewarding teaching and more effective learning. Originality/value – This study is one of the first to examine the use and benefits of video tutorials as a means of developing independent learning skills in accountancy students – addressing a key concern within the profession.

Patterns and transitions of query reformulation during web searching

Purpose – To investigate and identify the patterns of interaction between searchers and search engine during web searching. Design/methodology/approach – The authors examined 2,465,145 interactions from 534,507 users of Dogpile.com submitted on May 6, 2005, and compared query reformulation patterns. They investigated the type of query modifications and query modification transitions within sessions. Findings – The paper identifies three strong query reformulation transition patterns: between specialization and generalization; between video and audio, and between content change and system assistance. In addition, the findings show that web and images content were the most popular media collections. Originality/value – This research sheds light on the more complex aspects of web searching involving query modifications.

Measuring bitrate and quality trade-off in a fast region-of-interest based video coding

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).

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Energy use, indoor temperature and possible adaptation strategies for air-conditioned office buildings in face of global warming

This paper discusses and summarises a recent systematic study on the implication of global warming on air conditioned office buildings in Australia. Four areas are covered, including analysis of historical weather data, generation of future weather data for the impact study of global warming, projection of building performance under various global warming scenarios, and evaluation of various adaptation strategies under 2070 high global warming conditions. Overall, it is found that depending on the assumed future climate scenarios and the location considered, the increase of total building energy use for the sample Australian office building may range from 0.4 to 15.1%. When the increase of annual average outdoor temperature exceeds 2 °C, the risk of overheating will increase significantly. However, the potential overheating problem could be completely eliminated if internal load density is significantly reduced.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

Why the long face?

In this video, a male voice recites a script comprised entirely of jokes. Words flash on screen in time with the spoken words. Sometimes the two sets of words match, and sometimes they differ. This work examines processes of signification. It emphasizes disruption and disconnection as fundamental and generative operations in making meaning. Extending on post-structural and deconstructionist ideas, this work questions the relationship between written and spoken words. By deliberately confusing the signifying structures of jokes and narratives, it questions the sites and mechanisms of comprehension, humour and signification.

Volume estimation from multiplanar 2D ultrasound images using a remote electromagnetic position and orientation sensor

A system is described for calculating volume from a sequence of multiplanar 2D ultrasound images. Ultrasound images are captured using a video digitising card (Hauppauge Win/TV card) installed in a personal computer, and regions of interest transformed into 3D space using position and orientation data obtained from an electromagnetic device (Polbemus, Fastrak). The accuracy of the system was assessed by scanning 10 water filled balloons (13-141 ml), 10 kidneys (147  200 ml) and 16 fetal livers (8  37 ml) in water using an Acuson 128XP/10 (5 MHz curvilinear probe). Volume was calculated using the ellipsoid, planimetry, tetrahedral and ray tracing methods and compared with the actual volume measured by weighing (balloons) and water displacement (kidneys and livers). The mean percentage error for the ray tracing method was 0.9 ± 2.4%, 2.7 ± 2.3%, 6.6 ± 5.4% for balloons, kidneys and livers, respectively. So far the system has been used clinically to scan fetal livers and lungs, neonate brain ventricles and adult prostate glands.

A Context Space Model for Detecting Anomalous Behaviour in Video Surveillance

Having a good automatic anomalous human behaviour detection is one of the goals of smart surveillance systems’ domain of research. The automatic detection addresses several human factor issues underlying the existing surveillance systems. To create such a detection system, contextual information needs to be considered. This is because context is required in order to correctly understand human behaviour. Unfortunately, the use of contextual information is still limited in the automatic anomalous human behaviour detection approaches. This paper proposes a context space model which has two benefits: (a) It provides guidelines for the system designers to select information which can be used to describe context; (b)It enables a system to distinguish between different contexts. A comparative analysis is conducted between a context-based system which employs the proposed context space model and a system which is implemented based on one of the existing approaches. The comparison is applied on a scenario constructed using video clips from CAVIAR dataset. The results show that the context-based system outperforms the other system. This is because the context space model allows the system to considering knowledge learned from the relevant context only.

Perceiving and pursuing novelty : a grounded theory of adolescent creativity

Creativity plays an increasingly important role in our personal, social, educational, and community lives. For adolescents, creativity can enable self-expression, be a means of pushing boundaries, and assist learning, achievement, and completion of everyday tasks. Moreover, adolescents who demonstrate creativity can potentially enhance their capacity to face unknown future challenges, address mounting social and ecological issues in our global society, and improve their career opportunities and contribution to the economy. For these reasons, creativity is an essential capacity for young people in their present and future, and is highlighted as a priority in current educational policy nationally and internationally. Despite growing recognition of creativity’s importance and attention to creativity in research, the creative experience from the perspectives of the creators themselves and the creativity of adolescents are neglected fields of study. Hence, this research investigated adolescents’ self-reported experiences of creativity to improve understandings of their creative processes and manifestations, and how these can be supported or inhibited. Although some aspects of creativity have been extensively researched, there were no comprehensive, multidisciplinary theoretical frameworks of adolescent creativity to provide a foundation for this study. Therefore, a grounded theory methodology was adopted for the purpose of constructing a new theory to describe and explain adolescents’ creativity in a range of domains. The study’s constructivist-interpretivist perspective viewed the data and findings as interpretations of adolescents’ creative experiences, co-constructed by the participants and the researcher. The research was conducted in two academically selective high schools in Australia: one arts school, and one science, mathematics, and technology school. Twenty adolescent participants (10 from each school) were selected using theoretical sampling. Data were collected via focus groups, individual interviews, an online discussion forum, and email communications. Grounded theory methods informed a process of concurrent data collection and analysis; each iteration of analysis informed subsequent data collection. Findings portray creativity as it was perceived and experienced by participants, presented in a Grounded Theory of Adolescent Creativity. The Grounded Theory of Adolescent Creativity comprises a core category, Perceiving and Pursuing Novelty: Not the Norm, which linked all findings in the study. This core category explains how creativity involved adolescents perceiving stimuli and experiences differently, approaching tasks or life unconventionally, and pursuing novel ideas to create outcomes that are not the norm when compared with outcomes by peers. Elaboration of the core category is provided by the major categories of findings. That is, adolescent creativity entailed utilising a network of Sub-Processes of Creativity, using strategies for Managing Constraints and Challenges, and drawing on different Approaches to Creativity – adaptation, transfer, synthesis, and genesis – to apply the sub-processes and produce creative outcomes. Potentially, there were Effects of Creativity on Creators and Audiences, depending on the adolescent and the task. Three Types of Creativity were identified as the manifestations of the creative process: creative personal expression, creative boundary pushing, and creative task achievement. Interactions among adolescents’ dispositions and environments were influential in their creativity. Patterns and variations of these interactions revealed a framework of four Contexts for Creativity that offered different levels of support for creativity: high creative disposition–supportive environment; high creative disposition–inhibiting environment; low creative disposition–supportive environment; and low creative disposition–inhibiting environment. These contexts represent dimensional ranges of how dispositions and environments supported or inhibited creativity, and reveal that the optimal context for creativity differed depending on the adolescent, task, domain, and environment. This study makes four main contributions, which have methodological and theoretical implications for researchers, as well as practical implications for adolescents, parents, teachers, policy and curriculum developers, and other interested stakeholders who aim to foster the creativity of adolescents. First, this study contributes methodologically through its constructivist-interpretivist grounded theory methodology combining the grounded theory approaches of Corbin and Strauss (2008) and Charmaz (2006). Innovative data collection was also demonstrated through integration of data from online and face-to-face interactions with adolescents, within the grounded theory design. These methodological contributions have broad applicability to researchers examining complex constructs and processes, and with populations who integrate multimedia as a natural form of communication. Second, applicable to creativity in diverse domains, the Grounded Theory of Adolescent Creativity supports a hybrid view of creativity as both domain-general and domain-specific. A third major contribution was identification of a new form of creativity, educational creativity (ed-c), which categorises creativity for learning or achievement within the constraints of formal educational contexts. These theoretical contributions inform further research about creativity in different domains or multidisciplinary areas, and with populations engaged in formal education. However, the key contribution of this research is that it presents an original Theory and Model of Adolescent Creativity to explain the complex, multifaceted phenomenon of adolescents’ creative experiences.