Community engagement for development and application of 3D visualisation models : a two edged

Background: SEQ Catchments Ltd and QUT are collaborating on groundwater investigations in the SE Qld region, which utilise community engagement and 3D Visualisation methodologies. The projects, which have been funded by the Australian Government’s NHT and Caring for our Country programmes, were initiated from local community concerns regarding groundwater sustainability and quality in areas where little was previously known. ----- Objectives: Engage local and regional stakeholders to tap all available sources of information;•Establish on-going (2 years +) community-based groundwater / surface water monitoring programmes;•Develop 3D Visualisation from all available data; and•Involve, train and inform the local community for improved on-ground land and water use management. ----- Results and findings: Respectful community engagement yielded information, access to numerous monitoring sites and education opportunities at low cost, which would otherwise be unavailable. A Framework for Community-Based Groundwater Monitoring has been documented (Todd, 2008).A 3D visualisation models have been developed for basaltic settings, which relate surface features familiar to the local community with the interpreted sub-surface hydrogeology. Groundwater surface movements have been animated and compared to local rainfall using the time-series monitoring data.An important 3D visualisation feature of particular interest to the community was the interaction between groundwater and surface water. This factor was crucial in raising awareness of potential impacts of land and water use on groundwater and surface water resources.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Dynamic Performance Measures for Object Tracking Systems

Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

The emotional manipulation-psychopathy nexus : relationships with emotional intelligence, alexithymia, and ethical position

This research examined for the first time the relationship between emotional manipulation, emotional intelligence, and primary and secondary psychopathy. As predicted, in Study 1 (N = 73), emotional manipulation was related to both primary and secondary psychopathy. Only secondary psychopathy was related to perceived poor emotional skills. Secondary psychopathy was also related to emotional concealment. Emotional intelligence was negatively related to perceived poor emotional skills, emotional concealment, and primary and secondary psychopathy. In Study 2 (N = 275), two additional variables were included: alexithymia and ethical position. It was found that for males, primary psychopathy and emotional intelligence predicted emotional manipulation, while for females emotional intelligence acted as a suppressor, and ethical idealism and secondary psychopathy were additional predictors. For males, emotional intelligence and alexithymia were related to perceived poor emotional skills, while for females emotional intelligence, but not alexithymia, predicted perceived poor emotional skills, with ethical idealism acting as a suppressor. For both males and females, alexithymia predicted emotional concealment. These findings suggest that the mechanisms behind the emotional manipulation–psychopathy relationship differ as a function of gender. Examining the different aspects of emotional manipulation as separate but related constructs may enhance understanding of the construct of emotional manipulation.

Computational fluid dynamics for improved bioreactor design and 3D culture

The complex relationship between the hydrodynamic environment and surrounding tissues directly impacts on the design and production of clinically useful grafts and implants. Tissue engineers have generally seen bioreactors as 'black boxes' within which tissue engineering constructs (TECs) are cultured. It is accepted that a more detailed description of fluid mechanics and nutrient transport within process equipment can be achieved by using computational fluid dynamics (CFD) technology. This review discusses applications of CFD for tissue engineering-related bioreactors -- fluid flow processes have direct implications on cellular responses such as attachment, migration and proliferation. We conclude that CFD should be seen as an invaluable tool for analyzing and visualizing the impact of fluidic forces and stresses on cells and TECs.

Modeling corneal surfaces with three-dimensional basis functions

Purpose: To ascertain the effectiveness of object-centered three-dimensional representations for the modeling of corneal surfaces. Methods: Three-dimensional (3D) surface decomposition into series of basis functions including: (i) spherical harmonics, (ii) hemispherical harmonics, and (iii) 3D Zernike polynomials were considered and compared to the traditional viewer-centered representation of two-dimensional (2D) Zernike polynomial expansion for a range of retrospective videokeratoscopic height data from three clinical groups. The data were collected using the Medmont E300 videokeratoscope. The groups included 10 normal corneas with corneal astigmatism less than −0.75 D, 10 astigmatic corneas with corneal astigmatism between −1.07 D and 3.34 D (Mean = −1.83 D, SD = ±0.75 D), and 10 keratoconic corneas. Only data from the right eyes of the subjects were considered. Results: All object-centered decompositions led to significantly better fits to corneal surfaces (in terms of the RMS error values) than the corresponding 2D Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters (2, 4, 6, and 8 mm), and model orders (4th to 10th radial orders) The best results (smallest RMS fit error) were obtained with spherical harmonics decomposition which lead to about 22% reduction in the RMS fit error, as compared to the traditional 2D Zernike polynomials. Hemispherical harmonics and the 3D Zernike polynomials reduced the RMS fit error by about 15% and 12%, respectively. Larger reduction in RMS fit error was achieved for smaller corneral diameters and lower order fits. Conclusions: Object-centered 3D decompositions provide viable alternatives to traditional viewer-centered 2D Zernike polynomial expansion of a corneal surface. They achieve better fits to videokeratoscopic height data and could be particularly suited to the analysis of multiple corneal measurements, where there can be slight variations in the position of the cornea from one map acquisition to the next.

Using Ownership to Reason About Inherent Parallelism in Object-Oriented Programs

With the emergence of multi-cores into the mainstream, there is a growing need for systems to allow programmers and automated systems to reason about data dependencies and inherent parallelismin imperative object-oriented languages. In this paper we exploit the structure of object-oriented programs to abstract computational side-effects. We capture and validate these effects using a static type system. We use these as the basis of sufficient conditions for several different data and task parallelism patterns. We compliment our static type system with a lightweight runtime system to allow for parallelization in the presence of complex data flows. We have a functioning compiler and worked examples to demonstrate the practicality of our solution.

Collaborative business process modeling using 3D virtual environments

Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists involved in the process modeling. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. Some systems have been developed to support collaborative process modeling, all of which use traditional 2D interfaces. We present an environment for collaborative process modeling, using 3D virtual environment technology. We make use of avatar instantiations of user ego centres, to allow for the spatial embodiment of the user with reference to the process model. We describe an innovative prototype collaborative process modeling approach, implemented as a modeling environment in Second Life. This approach leverages the use of virtual environments to provide user context for editing and collaborative exercises. We present a positive preliminary report on a case study, in which a test group modelled a business process using the system in Second Life.

The osteogenic differentiation of adipose tissue-derived precursor cells in A 3D scaffold/matrix environment

Abstract: This paper details an in-vitro study using human adipose tissue-derived precursor/stem cells (ADSCs) in three-dimensional (3D) tissue culture systems. ADSCs from 3 donors were seeded onto NaOH-treated medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffolds with two different matrix components; fibrin glue and lyophilized collagen. ADSCs within these scaffolds were then induced to differentiate along the osteogenic lineage for a 28-day period and various assays and imaging techniques were performed at Day 1, 7, 14, 21 and 28 to assess and compare the ADSC’s adhesion, viability, proliferation, metabolism and differentiation along the osteogenic lineage when cultured in the different scaffold/matrix systems. The ADSC cells were proliferative in both collagen and fibrin mPCL-TCP scaffold systems with a consistently higher cell number (by comparing DNA amounts) in the induced group over the non-induced groups for both scaffold systems. In response to osteogenic induction, these ADSCs expressed elevated osteocalcin, alkaline phosphatase and osteonectin levels. Cells were able to proliferate within the pores of the scaffolds and form dense cellular networks after 28 days of culture and induction. The successful cultivation of osteogenic by FDM process manufactured ADSCs within a 3D matrix comprising fibrin glue or collagen, immobilized within a robust synthetic scaffold is a promising technique which should enhance their potential usage in the regenerative medicine arena, such as bone tissue engineering.

Design and evaluation of an MRI compatible axial compression device for 3D assessment of spinal deformity and flexibility

Magnetic Resonance Imaging (MRI) offers a valuable research tool for the assessment of 3D spinal deformity in AIS, however the horizontal patient position imposed by conventional scanners removes the axial compressive loading on the spine which is an important determinant of deformity shape and magnitude in standing scoliosis patients. The objective of this study was to design, construct and test an MRI compatible compression device for research into the effect of axial loading on spinal deformity using supine MRI scans. The compression device was designed and constructed, consisting of a vest worn by the patient, which was attached via straps to a pneumatically actuated footplate. An applied load of 0.5 x bodyweight was remotely controlled by a unit in the scanner operator’s console. The entire device was constructed using non-metallic components for MRI compatibility. The device was evaluated by performing unloaded and loaded supine MRI scans on a series of 10 AIS patients. The study concluded that an MRI compatible compression device had been successfully designed and constructed, providing a research tool for studies into the effect of axial loading on 3D spinal deformity in scoliosis. The 3D axially loaded MR imaging capability developed in this study will allow future research investigations of the effect of axial loading on spinal rotation, and for imaging the response of scoliotic spinal tissues to axial loading.

3D lung and rib cage reconstruction using low dose CT scans of adolescent idiopathic scoliosis pre and post anterior thoracoscopic correction

Adolescent Idiopathic Scoliosis (AIS) has been associated with reduced pulmonary function believed to be due to a restriction of lung volume by the deformed thoracic cavity. A recent study by our group examined the changes in lung volume pre and post anterior thoracoscopic scoliosis correction using pulmonary function testing (1), however the anatomical changes in ribcage shape and left/right lung volume after thoracoscopic surgery which govern overall respiratory capacity are unknown. The aim of this study was to use 3D rendering from CT scan data to compare lung and ribcage anatomical changes from pre to two years post thoracoscopic anterior scoliosis correction. The study concluded that 3D volumetric reconstruction from CT scans is a powerful means of evaluating changes in pulmonary and thoracic anatomy following surgical AIS correction. Most likely, lung volume changes following thoracoscopic scoliosis correction are multifactorial and affected by changes in height (due to residual growth), ribcage shape, diaphragm positioning, Cobb angle correction in the thoracic spine. Further analysis of the 3D reconstructions will be performed to assess how each of these factors affect lung volume in this patient cohort.

Fast and robust stereo object recognition for spheres

The paper presents a fast and robust stereo object recognition method. The method is currently unable to identify the rotation of objects. This makes it very good at locating spheres which are rotationally independent. Approximate methods for located non-spherical objects have been developed. Fundamental to the method is that the correspondence problem is solved using information about the dimensions of the object being located. This is in contrast to previous stereo object recognition systems where the scene is first reconstructed by point matching techniques. The method is suitable for real-time application on low-power devices.

The Sun gives without ever receiving

A small scale sculpture that contributes towards my ongoing explorations into how our collective ability to sustain (the future) is as much a cultural problematic as it is an economic or technological one. The curatorial brief of the project was a technical one - in that each curated artist was to design a piece in CAD suitable for 3D resin printing - The object should be entirely generated through 3D visualisation and modelling tools and should be machined and shipped within the dimensions of 6cm x 6cm x 6cm. My design for this brief was influenced by recent research I had conducted in Mildura in the Sunraysia irrigated region of NW Victoria. Each name set within the work is an Australian soldier/settler – who, on returning from the ‘Great War’ was duly awarded a ‘block’ in Australia’s new inland irrigated settlements - with the explicit task of clearing it to plant and reap. Through their concerted and well-intentioned efforts, these workers began to profoundly re-shape Australia’s marginal country - inadvertently presaging the bleak future faced today by many of Australia’s inland lands and river systems. Furthermore, through that time's predominant colonial conception of ‘terra nullius’ (this land is unoccupied and therefore free to be claimed) they each played a small but formative part in building the profound cultural divide between land and peoples that still haunts Australia today. THE EXHIBITION: Inside Out is a compelling international touring exhibition featuring forty-six miniature sculptures produced in resin using 3D printing technologies. Developments in virtual computer visualisation and integrated digital technologies are giving contemporary makers new insight and opportunities to create objects and forms which were previously impossible to produce or difficult to envisage. The exhibition is the result of collaboration between the Art Technology Coalition, the University of Technology Sydney and RMIT University in Australia along with De Montfort University, Manchester Metropolitan University and Dartington College of Arts at University College Falmouth in the United Kingdom.