A critical assessment of the Australian OHS accreditation system's "Body of Knowledge (BoK)"

In response to an increasing perception of poor OHS consultancy quality amongst the Australian public, regulator and OHS professionals, the Safety Institute Australia (SIA) was tasked by the Victorian government to establish an accreditation process for OHS professionals. The OHS accreditation board decided to base its accreditation on a core "body of knowledge" (BoK), against which applicants are assesssed. While the foundation and structure of the BoK is unclear, the BoK consists of a collection of essays from a variety of invited authors. The BoK comprises about 811 pages in 34 chapters, with significant redundancy and considerable subjective components. The SIA BoK is benchmarked against two international best-practices, the German "Core Definition, Object Catalog and Research Domains of Labour Science (Ergonomics)" (Luzcak, Volpert, Raeithel & Schwier, 1989)(100 pages) and the American "Core Competency Model" for the "Master's Degree in Public Health" (Association of Schools of Public Health, 2006) (21 pages). Both "core definition" and "core competency model" are on a comparative level to the BoK. While the German expert panel consisted of 14 eminent professors, the American panel consisted of 135 members, organized in 6 groups chaired by discipline leading academics. The Australian approach employed a broad approach, where 137 professionals, consultants, emerging academics and academics contributed to 8 workshops. Both the German and the American panels maintained an open communication amongst members and with the discipline community throughout the process, whereas SIA applied an open and directed peer-review process. Moreover, the German process involved an analysis of all congress content and journal publications in the scientific domain in a set timeframe, which were then systematically clustered. These results were further expanded by structured interviews with 38 professors in the discpline, grasping their research and teaching practice. The American workgroup however assumed core scientific areas, underlying the domain. Based upon the a-priori assumption, they then established well defined competencies across all areas using a modified Delphi process. Although the BoK attempts to explore the knowledge in the OHS domain without an imposed structure in a bottom-up approach, it does not result in a structured systematic of the science. We conclude that the outcome of the German, rigorous academic approach, and the US American democratic approach under unambiguous academic leadership both outperform the Australian advocacy group approach. This product was determined for both structure and content of the taxonomy delivered through the processes.

Accuracy of weight status perception in contemporary Australian children and adolescents

Aim: To explore weight status perception and its relation to actual weight status in a contemporary cohort of 5- to 17-year-old children and adolescents. Methods: Body mass index (BMI), derived from height and weight measurements, and perception of weight status (‘too thin’, ‘about right’ and ‘too fat’) were evaluated in 3043 participants from the Healthy Kids Queensland Survey. In children less than 12 years of age, weight status perception was obtained from the parents, whereas the adolescents self-reported their perceived weight status. Results: Compared with measured weight status by established BMI cut-offs, just over 20% of parents underestimated their child's weight status and only 1% overestimated. Adolescent boys were more likely to underestimate their weight status compared with girls (26.4% vs. 10.2%, P < 0.05) whereas adolescent girls were more likely to overestimate than underestimate (11.8% vs. 3.4%, P < 0.05). Underestimation was greater by parents of overweight children compared with those of obese children, but still less than 50% of parents identified their obese child as ‘too fat’. There was greater recognition of overweight status in the adolescents, with 83% of those who were obese reporting they were ‘too fat’. Conclusion: Whilst there was a high degree of accuracy of weight status perception in those of healthy weight, there was considerable underestimation of weight status, particularly by parents of children who were overweight or obese. Strategies are required that enable parents to identify what a healthy weight looks like and help them understand when intervention is needed to prevent further weight gain as the child gets older.

Image segmentation and pose estimation of humans in video

This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

Body stories

This research is in the field of arts education. Eisner claims that ‘teachers rarely view themselves as artists’ (Taylor, 1993:21). Situating professional dance artists and teacher-artists (Mc Lean, 2009) in close proximity to classroom dance teachers, spatially, through a shared rehearsal studio and creatively, by engaging them in a co-artistry approach, allows participants to map unique and new creative processes, kinaesthetically and experientially. This pratice encourages teachers to attune and align themselves with artists’ states of mind and enables them to nurture both their teacher-self and their artist-self (Lichtenstein 2009). The research question was: can interactions between professional dance artists, teacher-artists (Mc Lean, 2009) and classroom dance teachers change classroom dance teachers’ self-perceptions? The research found that Artists in Residence projects provide up-skilling in situ for classroom dance teachers, and give credence to the act of art making for classroom dance teachers within their peer context, positively enhancing their self-image and promoting self-identification as ‘teacher-artists’ (Mc Lean, 2009). This project received an Artist in Residence Grant (an Australia Council for the Arts, Education Queensland and Queensland Arts Council partnership). The research findings were chosen for inclusion in the Queensland Performing Arts Complex program, Feet First: an invitation to dance, 2013 and selected for inclusion on the Creative Campus website, http://www.creative-campus.org.uk.

Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

Datasets for the evaluation of multi-sensor perception in natural environments with challenging conditions

This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

Sensor Data Integrity : Multi-Sensor Perception for Unmanned Ground Vehicles

This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

The Marulan data sets: multi-sensor perception in a natural environment with challenging conditions

In this paper we present large, accurately calibrated and time-synchronized data sets, gathered outdoors in controlled and variable environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. These include four 2D laser scanners, a radar scanner, a color camera and an infrared camera. It provides a full description of the system used for data collection and the types of environments and conditions in which these data sets have been gathered, which include the presence of airborne dust, smoke and rain.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Towards reliable perception for unmanned ground vehicles in challenging conditions

This work aims to promote reliability and integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicle (UGV) autonomy. For this purpose, a comprehensive UGV system, comprising many different exteroceptive and proprioceptive sensors has been built. The first contribution of this work is a large, accurately calibrated and synchronised, multi-modal data-set, gathered in controlled environmental conditions, including the presence of dust, smoke and rain. The data have then been used to analyse the effects of such challenging conditions on perception and to identify common perceptual failures. The second contribution is a presentation of methods for mitigating these failures to promote perceptual integrity in adverse environmental conditions.

Did you see that? Dissociating advanced visual information and ball flight constrains perception and action processes during one-handed catching

The integration of separate, yet complimentary, cortical pathways appears to play a role in visual perception and action when intercepting objects. The ventral system is responsible for object recognition and identification, while the dorsal system facilitates continuous regulation of action. This dual-system model implies that empirically manipulating different visual information sources during performance of an interceptive action might lead to the emergence of distinct gaze and movement pattern profiles. To test this idea, we recorded hand kinematics and eye movements of participants as they attempted to catch balls projected from a novel apparatus that synchronised or de-synchronised accompanying video images of a throwing action and ball trajectory. Results revealed that ball catching performance was less successful when patterns of hand movements and gaze behaviours were constrained by the absence of advanced perceptual information from the thrower's actions. Under these task constraints, participants began tracking the ball later, followed less of its trajectory, and adapted their actions by initiating movements later and moving the hand faster. There were no performance differences when the throwing action image and ball speed were synchronised or de-synchronised since hand movements were closely linked to information from ball trajectory. Results are interpreted relative to the two-visual system hypothesis, demonstrating that accurate interception requires integration of advanced visual information from kinematics of the throwing action and from ball flight trajectory.