Report on Red Light Camera Program: Operation from July 1988 to December 1989

EXECUTIVE SUMMARY (excerpts) The red light camera (RLC) program commenced in July 1988, with five cameras operating at 15 sites in metropolitan Adelaide. This report deals with the first eighteen months of operation, to December 1989. A number of recommendations have been made… PROGRAM EVALUATION … In 1989 dollars, the program was estimated to have achieved an accident reduction benefit of $1.4m in the first 12 months of operation, which is almost twice the benefit expected using the assumptions made when selecting the sites. (There are 8 recommendations, mostly specific to the particular program characteristics)

The Red Light Camera Evaluation - Interim Report - July 1985

Red light cameras were introduced in August 1983 to deter run-the-red offences and therefore to reduce the incidence of right-angle accidents at signalised intersections in Melbourne. This report was prepared after two years of operation of the program. It provides a detailed account of the technical aspects of the program, but does not provide any detailed, evaluative analyses of accident data.

The influence of the elements of procedural justice and speed camera enforcement on young novice driver self-reported speeding

Road policing is an important tool used to modify road user behaviour. While other theories, such as deterrence theory, are significant in road policing, there may be a role for using procedural justice as a framework to improve outcomes in common police citizen interactions such as traffic law enforcement. This study, using a sample of 237 young novice drivers, considered how the four elements of procedural justice (voice, neutrality, respect and trustworthiness) were perceived in relation to two forms of speed enforcement: point-to-point (or average) speed and mobile speed cameras. Only neutrality was related to both speed camera types suggesting that it may be possible to influence behaviour by emphasising one or more elements, rather than using all components of procedural justice. This study is important as it indicates that including at least some elements of procedural justice in more automated policing encounters can encourage citizen compliance.

Tracking people in 3D using position, size and shape

This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

Documentary practice in a participatory culture

Debates concerning the veracity, ethics and politics of the documentary form circle endlessly around the function of those who participate in it, and the meaning attributed to their participation. Great significance is attached to the way that documentary filmmakers do or do not participate in the world they seek to represent, just as great significance is attached to those subjects whose participation extends beyond playing the part of eyewitness or expert, such that they become part of the very filmmaking process itself. This Ph.D. explores the interface between documentary practice and participatory culture by looking at how their practices, discursive fields and histories intersect, but also by looking at how participating in one might mean participating in the other. In short, the research is an examination of participatory culture through the lens of documentary practice and documentary criticism. In the process, however, this examination of participatory culture will in turn shed light on documentary thinking, especially the meaning and function of ‘the participant’ in contemporary documentary practice. A number of ways of conceiving of participation in documentary practice are discussed in this research, but one of the ideas that gives purpose to that investigation is the notion that the participant in contemporary documentary practice is someone who belongs to a participatory culture in particular. Not only does this mean that those subjects who play a part in a documentary are already informed by their engagement with a range of everyday media practices before the documentary apparatus arrives, the audience for such films are similarly informed and engaged. This audience have their own expectations about how they should be addressed by media producers in general, a fact that feeds back into their expectations about participatory approaches to documentary practice too. It is the ambition of this research to get closer to understanding the relationship between participants in the audience, in documentary and ancillary media texts, as well as behind the camera, and to think about how these relationships constitute a context for the production and reception of documentary films, but also how this context might provide a model for thinking about participatory culture itself. One way that documentary practice and participatory culture converge in this research is in the kind of participatory documentary that I call the ‘Camera Movie’, a narrow mode of documentary filmmaking that appeals directly to contemporary audiences’ desires for innovation and participation, something that is achieved in this case by giving documentary subjects control of the camera. If there is a certain inevitability about this research having to contend with the notion of the ‘participatory documentary’, the ‘participatory camera’ also emerges strongly in this context, especially as a conduit between producer and consumer. Making up the creative component of this research are two documentaries about the reality television event Band In A Bubble, and participatory media practices more broadly. The single-screen film, Hubbub , gives form to the collective intelligence and polyphonous voice of contemporary audiences who must be addressed and solicited in increasingly innovative ways. One More Like That is a split-screen, DVD-Video with alternate audio channels selected by a user who thereby chooses who listens and who speaks in the ongoing conversation between media producers and media consumers. It should be clear from the description above that my own practice does not extend to highly interactive, multi-authored or web-enabled practices, nor the distributed practices one might associate with social media and online collaboration. Mine is fundamentally a single authored, documentary video practice that seeks to analyse and represent participatory culture on screen, and for this reason the Ph.D. refrains from a sustained discussion of the kinds of collaborative practices listed above. This is not to say that such practices don’t also represent an important intersection of documentary practice and participatory culture, they simply represent a different point of intersection. Being practice-led, this research takes its procedural cues from the nature of the practice itself, and sketches parameters that are most enabling of the idea that the practice sets the terms of its own investigation.

Love at first sight : Sanja Pahoki

I am a landscape architect, a non-photographer, and in reviewing this exhibition, it seems that in a critical discourse on photography the nature of the view and its relation to the observer (presumably the camera) is inevitably a key focus of creative inquiry, in an epistemological sense. In conducting such a review, of 'self-portraits' by 'female photographers' in relation to 'the landscape', one cannot help but ask what priority this critique should allocate to each of these conceptual agendas, quite apart from the simple formal quality of the individual pieces themselves. Analytically, each could form the axes of a matrix that might allow for a number of quite different permutations and therefore differently conclusive commentaries on the others: the view vs landscape; the view vs sexuality; the self-portrait vs the landscape picture. All of these would be productive in their own right and each is alluded to in the works themselves and in the narrative of the catalogue. Considering this range of possible permutations, this show is certainly rich and this richness sits well with the relative formal saturation of the images themselves.

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.

Crowd Counting Using Multiple Local Features

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.

Bearing-only SLAM : a vision-based navigation system for autonomous robots

To navigate successfully in a previously unexplored environment, a mobile robot must be able to estimate the spatial relationships of the objects of interest accurately. A Simultaneous Localization and Mapping (SLAM) sys- tem employs its sensors to build incrementally a map of its surroundings and to localize itself in the map simultaneously. The aim of this research project is to develop a SLAM system suitable for self propelled household lawnmowers. The proposed bearing-only SLAM system requires only an omnidirec- tional camera and some inexpensive landmarks. The main advantage of an omnidirectional camera is the panoramic view of all the landmarks in the scene. Placing landmarks in a lawn field to define the working domain is much easier and more flexible than installing the perimeter wire required by existing autonomous lawnmowers. The common approach of existing bearing-only SLAM methods relies on a motion model for predicting the robot’s pose and a sensor model for updating the pose. In the motion model, the error on the estimates of object positions is cumulated due mainly to the wheel slippage. Quantifying accu- rately the uncertainty of object positions is a fundamental requirement. In bearing-only SLAM, the Probability Density Function (PDF) of landmark position should be uniform along the observed bearing. Existing methods that approximate the PDF with a Gaussian estimation do not satisfy this uniformity requirement. This thesis introduces both geometric and proba- bilistic methods to address the above problems. The main novel contribu- tions of this thesis are: 1. A bearing-only SLAM method not requiring odometry. The proposed method relies solely on the sensor model (landmark bearings only) without relying on the motion model (odometry). The uncertainty of the estimated landmark positions depends on the vision error only, instead of the combination of both odometry and vision errors. 2. The transformation of the spatial uncertainty of objects. This thesis introduces a novel method for translating the spatial un- certainty of objects estimated from a moving frame attached to the robot into the global frame attached to the static landmarks in the environment. 3. The characterization of an improved PDF for representing landmark position in bearing-only SLAM. The proposed PDF is expressed in polar coordinates, and the marginal probability on range is constrained to be uniform. Compared to the PDF estimated from a mixture of Gaussians, the PDF developed here has far fewer parameters and can be easily adopted in a probabilistic framework, such as a particle filtering system. The main advantages of our proposed bearing-only SLAM system are its lower production cost and flexibility of use. The proposed system can be adopted in other domestic robots as well, such as vacuum cleaners or robotic toys when terrain is essentially 2D.

Particle emission factors during cooking activities

Exposure to particles emitted by cooking activities may be responsible for a variety of respiratory health effects. However, the relationship between these exposures and their subsequent effects on health cannot be evaluated without understanding the properties of the emitted aerosol or the main parameters that influence particle emissions during cooking. Whilst traffic-related emissions, stack emissions and ultrafine particle concentrations (UFP, diameter < 100 nm) in urban ambient air have been widely investigated for many years, indoor exposure to UFPs is a relatively new field and in order to evaluate indoor UFP emissions accurately, it is vital to improve scientific understanding of the main parameters that influence particle number, surface area and mass emissions. The main purpose of this study was to characterise the particle emissions produced during grilling and frying as a function of the food, source, cooking temperature and type of oil. Emission factors, along with particle number concentrations and size distributions were determined in the size range 0.006-20 m using a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). An infrared camera was used to measure the temperature field. Overall, increased emission factors were observed to be a function of increased cooking temperatures. Cooking fatty foods also produced higher particle emission factors than vegetables, mainly in terms of mass concentration, and particle emission factors also varied significantly according to the type of oil used.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

The impact of police speed enforcement practices on self-reported speeding: An exploration of the effects of visibility and mobility

Research has highlighted the relationship between vehicle speed and increased crash risk and severity. Evidence suggests that police speed enforcement, in particular speed camera operations, can be an effective tool for reducing traffic crashes. A quantitative survey of Queensland drivers (n = 852) was conducted to investigate the impact of police speed enforcement methods on self-reported speeding behaviour. Results indicate that visible enforcement was associated with significantly greater self-reported compliance than covert operations irrespective of the mobility of the approach, and the effects on behaviour were longer lasting. The mobility of operations appeared to be moderated the visibility of the approach. Specifically, increased mobility was associated with increase reported compliant behaviour, but only for covert operations, and increased longevity of reported compliant behaviour, but only for overt operations. The perceived effectiveness of various speed enforcement approaches are also analysed across a range of driving scenarios. Results are discussed in light of the small effect sizes. Recommendations for policy and future research are presented.

Diurnal variation of corneal shape and thickness

Purpose: To investigate associations between the diurnal variation in a range of corneal parameters, including anterior and posterior corneal topography, and regional corneal thickness. ----- Methods: Fifteen subjects had their corneas measured using a rotating Scheimpflug camera (Pentacam) every 3-7 hours over a 24-hour period. Anterior and posterior corneal axial curvature, pachymetry and anterior chamber depth were analysed. The best fitting corneal sphero-cylinder from the axial curvature, and the average corneal thickness for a series of different corneal regions were calculated. Intraocular pressure and axial length were also measured at each measurement session. Repeated measures ANOVA were used to investigate diurnal change in these parameters. Analysis of covariance was used to examine associations between the measured ocular parameters. ----- Results: Significant diurnal variation was found to occur in both the anterior and posterior corneal curvature and in the regional corneal thickness. Flattening of the anterior corneal best sphere was observed at the early morning measurement (p < 0.0001). The posterior cornea also underwent a significant steepening (p < 0.0001) and change in astigmatism 90/180° at this time. A significant swelling of the cornea (p < 0.0001) was also found to occur immediately after waking. Highly significant associations were found between the diurnal variation in corneal thickness and the changes in corneal curvature. ----- Conclusions: Significant diurnal variation occurs in the regional thickness and the shape of the anterior and posterior cornea. The largest changes in the cornea were typically evident upon waking. The observed non-uniform regional corneal thickness changes resulted in a steepening of the posterior cornea, and a flattening of the anterior cornea to occur at this time.