Formative evaluation for improving collaborative planning : a case study at the regional scale

In an earlier paper (Cameron & Johnson 2004) we introduced the idea of formative evaluation (or evaluation for development), the purpose of which is to provide information for improving planning programs and activities. This type of evaluation differs from the two other types: outcome evaluation which aims to judge the success or otherwise of a program; and evaluation for knowledge which seeks to contribute to theoretical work on planning processes and activities. In the earlier paper we also outlined the first stage of formative evaluation in the SEQ 2021 regional planning exercise showing how the process of planning for community engagement was modified in light of the evaluation findings. This current paper details the second stage of formative evaluation in which the collaborative planning component of SEQ 2021 was evaluated, as such it further demonstrates how formative evaluation can be used to improve planning programs. The evaluation findings also provide insights into strategies for more effective collaborative planning. We begin with an overview of collaborative approaches to regional planning, including the SEQ 2021 regional planning program. We then outline formal and informal evaluations of various collaborative regional planning exercises, including the predecessor of SEQ 2021 - SEQ 2001. This sets the scene for discussion of the approach used to evaluate the collaborative component of SEQ 2021. After outlining the main findings from the evaluation and the ways these findings were used to refine the collaborative planning process we conclude with a series of recommendations, relevant not only to SEQ 2021 but to other collaborative planning exercises

Recognising facial expressions with noisy data

Techniques to improve the automated analysis of natural and spontaneous facial expressions have been developed. The outcome of the research has applications in several fields including national security (eg: expression invariant face recognition); education (eg: affect aware interfaces); mental and physical health (eg: depression and pain recognition).

Investigating the factors influencing cyclist awareness and behaviour : an on-road study of cyclist situation awareness

Situation awareness, ones understanding of ‘what is going on’, is a critical commodity for road users. Although the concept has received much attention in the driving context, situation awareness in vulnerable road users, such as cyclists, remains unexplored. This paper presents the findings from an exploratory on-road study of cyclist situation awareness, the aim of which was to explore how cyclists develop situation awareness, what their situation awareness comprises, and what the causes of degraded cyclist situation awareness may be. Twenty participants cycled a pre-defined urban on-road study route. A range of data were collected, including verbal protocols, forward scene video and rear video, and a network analysis procedure was used to describe and assess cyclist situation awareness. The analysis produced a number of key findings regarding cyclist situation awareness, including the potential for cyclists’ awareness of other road users to be degraded due to additional situation awareness and decision making requirements that are placed on them in certain road situations. Strategies for improving cyclists’ situation awareness are discussed.

Robust vision-based underwater homing using self-similar landmarks

Next-generation autonomous underwater vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions.

GO423 - the second Game On / brIGDA Independant Game Symposium

GO423 was initiated in 2012 as part of a community effort to ensure the vitality of the Queensland Games Sector. In common with other industrialised nations, the game industry in Australia is a reasonably significant contributor to Gross National Product (GNP). Games are played in 92% of Australian homes and the average adult player has been playing them for at least twelve years with 26% playing for more than thirty years (Brand, 2011). Like the games and interactive entertainment industries in other countries, the Australian industry has its roots in the small team model of the 1980s. So, for example, Beam Software, which was established in Melbourne in 1980, was started by two people and Krome Studios was started in 1999 by three. Both these companies grew to employing over 100 people in their heydays (considered large by Antipodean standards), not by producing their own intellectual property (IP) but by content generation for off shore parent companies. Thus our bigger companies grew on a model of service provision and tended not to generate their own IP (Darchen, 2012). There are some no-table exceptions where IP has originated locally and been ac-quired by international companies but in the case of some of the works of which we are most proud, the Australian company took on the role of “Night Elf” – a convenience due to affordances of the time zone which allowed our companies to work while the parent companies slept in a different time zone. In the post GFC climate, the strong Australian dollar and the vulnerability of such service provision means that job security is virtually non-existent with employees invariably being on short-term contracts. These issues are exacerbated by the decline of middle-ground games (those which fall between the triple-A titles and the smaller games often produced for a casual audience). The response to this state of affairs has been the change in the Australian games industry to new recognition of its identity as a wider cultural sector and the rise (or return) of an increasing number of small independent game development companies. ’In-dies’ consist of small teams, often making games for mobile and casual platforms, that depend on producing at least one if not two games a year and who often explore more radical definitions of games as designed cultural objects. The need for innovation and creativity in the Australian context is seen as a vital aspect of the current changing scene where we see the emphasis on the large studio production model give way to an emerging cultural sector model where small independent teams are engaged in shorter design and production schedules driven by digital distribution. In terms of Quality of Life (QoL) this new digital distribution brings with it the danger of 'digital isolation' - a studio can work from home and deliver from home. Community events thus become increasingly important. The GO423 Symposium is a response to these perceived needs and the event is based on the understanding that our new small creative teams depend on the local community of practice in no small way. GO423 thus offers local industry participants the opportunity to talk to each other about their work, to talk to potential new members about their work and to show off their work in a small intimate situation, encouraging both feedback and support.

Real-time video event detection in crowded scenes using MPEG derived features : a multiple instance learning approach

This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

Interpersonal, intrapersonal, extrapersonal? Qualitatively investigating coordinative couplings between rowers in Olympic sculling

Coordinative couplings are commonly classified as interpersonal and intrapersonal. Interpersonal coordination is normally thought of as between organisms but a subset can also be considered where the co-actors movements are coupled to an environmental rhythm. This can be termed extrapersonal coordination. This study explores how coordination is achieved in a situation that demands that at least one actor makes use of extrapersonal sources. In this case multi-seat rowing, where one actor cannot see the other one behind them. A qualitative approach using experiential knowledge from expert rowers (N=9) and coaches (N=4) was used to examine how interpersonal coordination was achieved and maintained in 2 person rowing boats. It was reported that where possible, both rowers coordinated their movements by coupling with an invariant provided by the boat. This invariant is underpinned by perception of water flow past the boat; which is in turn used to determine changes in acceleration - 'rowing with the boat.' Bow seat also identified the rower in front and stroke seat identified the looming of the stern as viable alternative sources for coupling.

Developmental lessons from the Capricornia Arts Mob (CAM)

The Capricornia Arts Mob (CAM) is a collective of Aboriginal and Torres Strait Islander visual artists, sculptors, photographers, carvers and writers based in the Rockhampton region of Central Queensland. This paper explores the early development of CAM, identifies some of the lessons its members have learned about working together, and considers its role as a regional artists’ collective. The authors identify that traditional Indigenous practices, such as yarning and the sharing of food, have helped to facilitate the emergence of CAM as a vibrant, challenging, eclectic artistic family. They recognise the cultural challenges faced by the collective – including finding a culturally appropriate place to meet and work, and the cross-cultural issues that can emerge within Aboriginal and Torres Strait Islander groups. In just 18 months, CAM has held successful exhibitions and developed public artworks. It is a strong part of regional Queensland’s arts scene, which supports emerging artists and provides a space to celebrate and support Indigenous art.

Heritage language learning for Chinese Australians : the role of habitus

The relationship between Heritage Language and ethnic identity has gained significant research ground in social psychological and poststructural scholarship, with empirical evidence largely emerging from the North American settings. There is little pertinent sociological work conducted outside North America. To fill this gap, this sociological study sets its scene in an Australian context. Drawing on Bourdieu’s notion of habitus, the study examines the contribution of Chinese Australians’ Chineseness to their Chinese Heritage Language proficiency. Two hundred and thirty young Chinese Australians completed the online survey. Results from multiple regression indicate that habitus of Chineseness is one of the significant predictors for the Chinese Heritage Language proficiency of these young people. The study makes a theoretical contribution to investigate ethnic identity – Heritage Language link through the notion of habitus and makes a methodological contribution to quantify this habitus.

Found in translation : debating the abstract elements of cultures through actor training styles

While the synthesis of acting methodologies in intercultural acting has been discussed at length, little discussion has focussed on the potential of diverse actor training styles to affect performance making and audience reception. This article explores a project where the abstract elements of the British and American cultures were translated in rehearsal and in production through the purposeful juxtaposition of two differing actor training styles: the British ‘traditional’ approach and the American Method. William Nicholson’s Shadowlands was produced by Crossbow Productions at the Brisbane Powerhouse in 2010. Nicholson’s play contains a discourse on the cultural cringe of British – American relations. As a research project, the production aimed to extend and augment audience experience of the socio-cultural tensions inherent in the play by juxtaposing two seemingly culturally inscribed approaches to acting. Actors were chosen who had been trained under a traditional conservatoire approach and the American Method. A brief overview of these acting approaches is followed by a discussion centred on the project. This article analyses how from the casting room to the rehearsal room to the mise en scene and into the audience discussions, cultural issues were articulated, translated and debated through the language of acting.

An evaluation of different features and learning models for anomalous event detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Hearing loss and a supportive tactile signal in a navigation system : effects on driving behavior and eye movements

An on-road study was conducted to evaluate a complementary tactile navigation signal on driving behaviour and eye movements for drivers with hearing loss (HL) compared to drivers with normal hearing (NH). 32 participants (16 HL and 16 NH) performed two preprogrammed navigation tasks. In one, participants received only visual information, while the other also included a vibration in the seat to guide them in the correct direction. SMI glasses were used for eye tracking, recording the point of gaze within the scene. Analysis was performed on predefined regions. A questionnaire examined participant's experience of the navigation systems. Hearing loss was associated with lower speed, higher satisfaction with the tactile signal and more glances in the rear view mirror. Additionally, tactile support led to less time spent viewing the navigation display.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Swimmer localization from a moving camera

At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

Advantages of exploiting projection structure for segmenting dense 3D point clouds

Timely and comprehensive scene segmentation is often a critical step for many high level mobile robotic tasks. This paper examines a projected area based neighbourhood lookup approach with the motivation towards faster unsupervised segmentation of dense 3D point clouds. The proposed algorithm exploits the projection geometry of a depth camera to find nearest neighbours which is time independent of the input data size. Points near depth discontinuations are also detected to reinforce object boundaries in the clustering process. The search method presented is evaluated using both indoor and outdoor dense depth images and demonstrates significant improvements in speed and precision compared to the commonly used Fast library for approximate nearest neighbour (FLANN) [Muja and Lowe, 2009].