Long-range stereo visual odometry for unmanned aerial vehicles

This thesis explored the utility of long-range stereo visual odometry for application on Unmanned Aerial Vehicles. Novel parameterisations and initialisation routines were developed for the long-range case of stereo visual odometry and new optimisation techniques were implemented to improve the robustness of visual odometry in this difficult scenario. In doing so, the applications of stereo visual odometry were expanded and shown to perform adequately in situations that were previously unworkable.

Functional MRI BOLD response to Tower of London performance of first-episode schizophrenia patients using cortical pattern matching

Due to its three-dimensional folding pattern, the human neocortex; poses a challenge for accurate co-registration of grouped functional; brain imaging data. The present study addressed this problem by; employing three-dimensional continuum-mechanical image-warping; techniques to derive average anatomical representations for coregistration; of functional magnetic resonance brain imaging data; obtained from 10 male first-episode schizophrenia patients and 10 age-matched; male healthy volunteers while they performed a version of the; Tower of London task. This novel technique produced an equivalent; representation of blood oxygenation level dependent (BOLD) response; across hemispheres, cortical regions, and groups, respectively, when; compared to intensity average co-registration, using a deformable; Brodmann area atlas as anatomical reference. Somewhat closer; association of Brodmann area boundaries with primary visual and; auditory areas was evident using the gyral pattern average model.; Statistically-thresholded BOLD cluster data confirmed predominantly; bilateral prefrontal and parietal, right frontal and dorsolateral; prefrontal, and left occipital activation in healthy subjects, while; patients’ hemispheric dominance pattern was diminished or reversed,; particularly decreasing cortical BOLD response with increasing task; difficulty in the right superior temporal gyrus. Reduced regional gray; matter thickness correlated with reduced left-hemispheric prefrontal/; frontal and bilateral parietal BOLD activation in patients. This is the; first study demonstrating that reduction of regional gray matter in; first-episode schizophrenia patients is associated with impaired brain; function when performing the Tower of London task, and supports; previous findings of impaired executive attention and working memory; in schizophrenia.

Visual control for automated aircraft collision avoidance systems

This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.

A neuronal topography of visual and acoustic fear conditioning within the amygdala

The lateral amygdala (LA) receives information from auditory and visual sensory modalities, and uses this information to encode lasting memories that predict threat. One unresolved question about the amygdala is how multiple memories, derived from different sensory modalities, are organized at the level of neuronal ensembles. We previously showed that fear conditioning using an auditory conditioned stimulus (CS) was spatially allocated to a stable topography of neurons within the dorsolateral amygdala (LAd) (Bergstrom et al, 2011). Here, we asked how fear conditioning using a visual CS is topographically organized within the amygdala. To induce a lasting fear memory trace we paired either an auditory (2 khz, 55 dB, 20 s) or visual (1 Hz, 0.5 s on/0.5 s off, 35 lux, 20 s) CS with a mild foot shock unconditioned stimulus (0.6 mA, 0.5 s). To detect learning-induced plasticity in amygdala neurons, we used immunohistochemistry with an antibody for phosphorylated mitogen-activated protein kinase (pMAPK). Using a principal components analysis-based approach to extract and visualize spatial patterns, we uncovered two unique spatial patterns of activated neurons in the LA that were associated with auditory and visual fear conditioning. The first spatial pattern was specific to auditory cued fear conditioning and consisted of activated neurons topographically organized throughout the LAd and ventrolateral nuclei (LAvl) of the LA. The second spatial pattern overlapped for auditory and visual fear conditioning and was comprised of activated neurons located mainly within the LAvl. Overall, the density of pMAPK labeled cells throughout the LA was greatest in the auditory CS group, even though freezing in response to the visual and auditory CS was equivalent. There were no differences detected in the number of pMAPK activated neurons within the basal amygdala nuclei. Together, these results provide the first basic knowledge about the organizational structure of two different fear engrams within the amygdala and suggest they are dissociable at the level of neuronal ensembles within the LA

IMU aided 3D visual odometry for car-like vehicles

We present a method for calculating odome- try in three-dimensions for car-like ground ve- hicles with an Ackerman-like steering model. In our approach we use the information from a single camera to derive the odometry in the plane and fuse it with roll and pitch informa- tion derived from an on-board IMU to extend to three-dimensions, thus providing odometric altitude as well as traditional x and y transla- tion. We have mounted the odometry module on a standard Toyota Prado SUV and present results from a car-park environment as well as from an off-road track.

"Rebirth: Combined art performance"--Shirin Madg & Sweet Sound Ensemble

Vanessa Mafe-Keane was invited to participate as choreographer in Iranian singer Shirin Madg 's project, Rebirth: Combined art performance. This project integrated singing, music, visual-art, film, dance and is based on the dissident poetry of female Iranian poet, Forough Farrokhzad. The choreographic dance movement focused on simple, lyrical, flowing classical dance forms that also incorporated everyday gestures and actions performed by two Queensland dancers, Caitlin MacKenzie and Abby Johnson. The choreographic intention was not to attempt to re-create Iranian dance practices instead, to draw inspiration and reference specific movement qualities. This was achieved through the subtle inclusion of spinning movements and focusing attention on the dancers’ arms and upper torso. This fusion became an underlying theme reflected throughout the choreographic component. Additionally, this project presented an opportunity to draw on past experiences and problem-solve ways to construct choreographic work where the dancers and the musical assemble group could be staged side by side. This experience highlighted differing approaches to rehearsal protocols within disciplines, the practicalities of staging different artists, understanding musical cues and the diversity of audience engagement. Performances: BEMAC Multicultural Centre, Brisbane 06 February 2015 and Helensvale Cultural Centre, Gold Coast 07 February 2015

Changing the game: The role of social media in overcoming old media's attention deficit toward women's sport

Social media is now an integral part of modern sports broadcasting, which combines old and new media into a redefined and multidimensional experience for fans. The popularity of social media has particular implications for professional women's sports due to this convergence, and may be utilised by organisations to address some of the issues women's sports face from a lack of traditional broadcast coverage. This article discusses Twitter activity surrounding the ANZ Championship netball competition and analyses the ways social media can help transcend the structural challenges that “old” media has placed on professional women's sports.

Examining the new product innovation – performance relationship: Optimizing the role of individual-level creativity and attention-to-detail

New product innovation has been identified as the key to firms' marketplace success, profit and survival. Yet, the failure rate for new products is high. Because of the high costs associated with new product development, there is considerable theoretical and managerial interest in how to minimize the high failure rates of new products and what separates new product winners from losers. This study focuses on individual level ambidexterity – namely head of the R&D departments' capacity to engage in creativity and attention-to-detail simultaneously, a skill involving different centers of attention, and relying on somewhat incompatible behaviors and processes. The ability to engage in these behaviors simultaneously is seen as being ambidextrous. Drawing from the data of 150 advanced manufacturing firms in India (gathered from one CEO and one head of the R&D department for each firm), the results show that when an individual head of R&D engages heavily only in creativity, too many new, risky ideas may come and when he/she engages heavily only in attention-to-detail, he/she may suffer through a lack of novel ideas. Both approaches limit individual's contribution to enhancing product innovation – financial performance relationship. The results also show that an individual head of R&D needs to engage in high levels creativity and attention-to-detail in the pursuit of enhancing product innovation to achieve superior financial performance.

Parallel attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real-time, using corners as object tokens. Corners are detected using the Harris corner detector, and local image-plane constraints are employed to solve the correspondence problem. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. Tracking is performed without the use of any 3-dimensional motion model. The technique is novel in that, unlike traditional feature-tracking algorithms where feature detection and tracking is carried out over the entire image-plane, here it is restricted to those areas most likely to contain-meaningful image structure. Two distinct types of instantiation regions are identified, these being the “focus-of-expansion” region and “border” regions of the image-plane. The size and location of these regions are defined from a combination of odometry information and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Implementation of the algorithm using T800 Transputers has shown that near-linear speedups are achievable, and that real-time operation is possible (half-video rate has been achieved using 30 processing elements).

Attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real time, using corners as object tokens. Local image-plane constraints are employed to solve the correspondence problem removing the need for a 3D motion model. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. The technique is novel in that feature detection and tracking is restricted to areas likely to contain meaningful image structure. Feature instantiation regions are defined from a combination of odometry informatin and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Preliminary experiments on a parallel (transputer) architecture indication that real-time operation is achievable.

Enhancing the teaching and learning of mathematical visual images

The literacy demands of mathematics are very different to those in other subjects (Gough, 2007; O'Halloran, 2005; Quinnell, 2011; Rubenstein, 2007) and much has been written on the challenges that literacy in mathematics poses to learners (Abedi and Lord, 2001; Lowrie and Diezmann, 2007, 2009; Rubenstein, 2007). In particular, a diverse selection of visuals typifies the field of mathematics (Carter, Hipwell and Quinnell, 2012), placing unique literacy demands on learners. Such visuals include varied tables, graphs, diagrams and other representations, all of which are used to communicate information.

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.