Surface engineering of reduced graphene oxide for controllable ambipolar flash memories

Tunable charge-trapping behaviors including unipolar charge trapping of one type of charge carrier and ambipolar trapping of both electrons and holes in a complementary manner is highly desirable for low power consumption multibit flash memory design. Here, we adopt a strategy of tuning the Fermi level of reduced graphene oxide (rGO) through self-assembled monolayer (SAM) functionalization and form p-type and n-type doped rGO with a wide range of manipulation on work function. The functionalized rGO can act as charge-trapping layer in ambipolar flash memories, and a dramatic transition of charging behavior from unipolar trapping of electrons to ambipolar trapping and eventually to unipolar trapping of holes was achieved. Adjustable hole/electron injection barriers induce controllable Vth shift in the memory transistor after programming operation. Finally, we transfer the ambipolar memory on flexible substrates and study their charge-trapping properties at various bending cycles. The SAM-functionalized rGO can be a promising candidate for next-generation nonvolatile memories.

Searching for semantic person queries using channel representations

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

On the use of optical flow for scene change detection and description

We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.

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.

Redundant sensing for localisation in outdoor industrial environments

We describe our experiences with automating a large fork-lift type vehicle that operates outdoors and in all weather. In particular, we focus on the use of independent and robust localisation systems for reliable navigation around the worksite. Two localisation systems are briefly described. The first is based on laser range finders and retro-reflective beacons, and the second uses a two camera vision system to estimate the vehicle’s pose relative to a known model of the surrounding buildings. We show the results from an experiment where the 20 tonne experimental vehicle, an autonomous Hot Metal Carrier, was conducting autonomous operations and one of the localisation systems was deliberately made to fail.

Exploiting parallax in panoramic capture to construct light fields

We show that the parallax motion resulting from non-nodal rotation in panorama capture can be exploited for light field construction from commodity hardware. Automated panoramic image capture typically seeks to rotate a camera exactly about its nodal point, for which no parallax motion is observed. This can be difficult or impossible to achieve due to limitations of the mounting or optical systems, and consequently a wide range of captured panoramas suffer from parallax between images. We show that by capturing such imagery over a regular grid of camera poses, then appropriately transforming the captured imagery to a common parameterisation, a light field can be constructed. The resulting four-dimensional image encodes scene geometry as well as texture, allowing an increasingly rich range of light field processing techniques to be applied. Employing an Ocular Robotics REV25 camera pointing system, we demonstrate light field capture,refocusing and low-light image enhancement.

Using viewer’s facial expression and heart rate for sports video highlights detection

Viewer interests, evoked by video content, can potentially identify the highlights of the video. This paper explores the use of facial expressions (FE) and heart rate (HR) of viewers captured using camera and non-strapped sensor for identifying interesting video segments. The data from ten subjects with three videos showed that these signals are viewer dependent and not synchronized with the video contents. To address this issue, new algorithms are proposed to effectively combine FE and HR signals for identifying the time when viewer interest is potentially high. The results show that, compared with subjective annotation and match report highlights, ‘non-neutral’ FE and ‘relatively higher and faster’ HR is able to capture 60%-80% of goal, foul, and shot-on-goal soccer video events. FE is found to be more indicative than HR of viewer’s interests, but the fusion of these two modalities outperforms each of them.

Slippage: Reclaiming personal family history through contemporary photomedia

This paper addresses the role of photography as a documentary medium and how this forms a basis for my practice-led studio investigations. In it, I will explore how photography is used to create histories and sustain specific notions of ‘legacy’ within the context of the family photo album. Family history is often based on stories to which the photo album provides a visual point of reference. Despite the ostensible ‘objectivity’ of the family photograph though it is nonetheless as subjective as the stories that surround it. In this way, the photo album perpetuates a hegemony of truth that obscures the fragmentary and highly selective nature of these documents and stories. The result is that every photo album implicitly documents the gaps or voids present in understandings of our own histories. Homi Bhabha refers to these kinds of voids as ‘disjunctive historical spaces’ – spaces of slippage that create the opportunity for new narratives and understandings to occur. Using Bhabha’s ideas as a chief point of reference, I will explore how these voids or gaps in information – and the opportunities for re-examination that they open up - can be explored through contemporary photomedia. Digital technologies such as camera phones and scanners generate a space in which photography’s own documentary conventions can be turned in on themselves to create a subterfuge. My current studio-based research involves using the scanner to navigate through my family’s sometimes-‘occulted’ history, in order to explore, document and recover my connection to this narrative. I am primarily interested in the scanner as a tool for capturing not simply surfaces, but objects, moments or movements in time. Objects or moments captured by the scanner can often be simultaneously distorted and consolidated, blurred and sharpened. This paper will propose that this ‘slippage’, literally expressed in the disruption of the pixelated field, can be used to create a space in which alternative readings or understandings of past events can be explored and new narratives produced.

Is the sun too bright in Queensland? An approach to robust outdoor colour beacon detection

Using cameras onboard a robot for detecting a coloured stationary target outdoors is a difficult task. Apart from the complexity of separating the target from the background scenery over different ranges, there are also the inconsistencies with direct and reflected illumination from the sun,clouds, moving and stationary objects. They can vary both the illumination on the target and its colour as perceived by the camera. In this paper, we analyse the effect of environment conditions, range to target, camera settings and image processing on the reported colours of various targets. The analysis indicates the colour space and camera configuration that provide the most consistent colour values over varying environment conditions and ranges. This information is used to develop a detection system that provides range and bearing to detected targets. The system is evaluated over various lighting conditions from bright sunlight, shadows and overcast days and demonstrates robust performance. The accuracy of the system is compared against a laser beacon detector with preliminary results indicating it to be a valuable asset for long-range coloured target detection.

Urban public space and the marginalisation of children and young people

In the 21st century city, public space for a range of users, but especially children and young people, has come under threat. Watson proposed that “public space itself has come under attack from several directions-thematisation, enclosure into malls and other controlled spaces, and privatisation, or from urban planning and design interventions to erase its uniqueness”. Largely as a result of these trends, Scott observed that “young urbanites form a marginalised age class movement is restricted, out of fear and distrust, within aims to protect, monitored by city surveillance methods within the security-obsessed fabric”. The use of public space by children and young people is a contentious issue in a number of countries and a range of measures deployed to control public space curtail the rights of children and young people to claim the space for their use through curfews, oppressive camera surveillance and at times, the unwarranted attentions of police and private security personnel.

Automatic image scaling for place recognition in changing environments

Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.

A determinism and desire: Some neurological processes in perceiving the design object

The environment moderates behaviour using a subtle language of ‘affordances’ and ‘behaviour-settings’. Affordances are environmental offerings. They are objects that demand action; a cliff demands a leap and binoculars demand a peek. Behaviour-settings are ‘places;’ spaces encoded with expectations and meanings. Behaviour-settings work the opposite way to affordances; they demand inhibition; an introspective demeanour in a church or when under surveillance. Most affordances and behaviour-settings are designed, and as such, designers are effectively predicting brain reactions. • Affordances are nested within, and moderated by behaviour-settings. Both trigger automatic neural responses (excitation and inhibition). These, for the best part cancel each other out. This balancing enables object recognition and allows choice about what action should be taken (if any). But when excitation exceeds inhibition, instinctive action will automatically commence. In positive circumstances this may mean laughter or a smile. In negative circumstances, fleeing, screaming or other panic responses are likely. People with poor frontal function, due to immaturity (childhood or developmental disorders) or due to hypofrontality (schizophrenia, brain damage or dementia) have a reduced capacity to balance excitatory and inhibitory impulses. For these people, environmental behavioural demands increase with the decline of frontal brain function. • The world around us is not only encoded with symbols and sensory information. Opportunities and restrictions work on a much more primal level. Person/space interactions constantly take place at a molecular scale. Every space we enter has its own special dynamic, where individualism vies for supremacy between the opposing forces of affordance-related excitation and the inhibition intrinsic to behaviour-settings. And in this context, even a small change–the installation of a CCTV camera can turn a circus to a prison. • This paper draws on cutting-edge neurological theory to understand the psychological determinates of the everyday experience of the designed environment.

Large scale monitoring of crowds and building utilisation: A new database and distributed approach

Public buildings and large infrastructure are typically monitored by tens or hundreds of cameras, all capturing different physical spaces and observing different types of interactions and behaviours. However to date, in large part due to limited data availability, crowd monitoring and operational surveillance research has focused on single camera scenarios which are not representative of real-world applications. In this paper we present a new, publicly available database for large scale crowd surveillance. Footage from 12 cameras for a full work day covering the main floor of a busy university campus building, including an internal and external foyer, elevator foyers, and the main external approach are provided; alongside annotation for crowd counting (single or multi-camera) and pedestrian flow analysis for 10 and 6 sites respectively. We describe how this large dataset can be used to perform distributed monitoring of building utilisation, and demonstrate the potential of this dataset to understand and learn the relationship between different areas of a building.

Robotic detection and tracking of Crown-Of-Thorns starfish

This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.

Improving monocular SLAM with altimeter hints for fixed-wing aircraft navigation and emergency landing

This paper presents a visual SLAM method for temporary satellite dropout navigation, here applied on fixed- wing aircraft. It is designed for flight altitudes beyond typical stereo ranges, but within the range of distance measurement sensors. The proposed visual SLAM method consists of a common localization step with monocular camera resectioning, and a mapping step which incorporates radar altimeter data for absolute scale estimation. With that, there will be no scale drift of the map and the estimated flight path. The method does not require simplifications like known landmarks and it is thus suitable for unknown and nearly arbitrary terrain. The method is tested with sensor datasets from a manned Cessna 172 aircraft. With 5% absolute scale error from radar measurements causing approximately 2-6% accumulation error over the flown distance, stable positioning is achieved over several minutes of flight time. The main limitations are flight altitudes above the radar range of 750 m where the monocular method will suffer from scale drift, and, depending on the flight speed, flights below 50 m where image processing gets difficult with a downwards-looking camera due to the high optical flow rates and the low image overlap.