Speed enforcement in China : national, provincial and city initiatives and their success

China is motorizing rapidly, with associated urban road development and extensive construction of motorways. Speeding accounts for about 10% of fatalities, which represents a large decrease from a peak of 17.2% in 2004. Speeding has been addressed at a national level through the introduction of laws and procedural requirements in 2004, in provinces either across all road types or on motorways, and at city level. Typically, documentation of speed enforcement programmes has taken place when new technology (i.e. speed cameras) is introduced, and it is likely that many programmes have not been documented or widely reported. In particular, the national legislation of 2004 and its implementation was associated with a large reduction in fatalities attributed to speeding. In Guangdong Province, after using speed detection equipment, motorway fatalities due to speeding in 2005 decreased by 32.5% comparing with 2004. In Beijing, the number of traffic monitoring units which were used to photograph illegal traffic activities such as traffic light violations, speeding and using bus lanes illegally increased to 1958 by April 1, 2009, and in the future such automated enforcement will become the main means of enforcement, expected to account for 60% of all traffic enforcement in Beijing. This paper provides a brief overview of the speeding enforcement programmes in China which have been documented and their successes.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas [Virtual presentation]

This proposal combines ethnographic techniques and discourse studies to investigating a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation referring to favelas which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project which all participants join to use photography and participatory audiovisual production as a tool for social change and raising consciousness. As cameras are not affordable for favelas dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against the lack of basic resources.

Participatory content creation and collective intelligence in Rio de Janeiro's favelas

This proposal combines ethnographic techniques and discourse studies to investigate a collective of people engaged with audiovisual productions who collaborate in Curta Favela’s workshops in Rio de Janeiro’s favelas. ‘Favela’ is often translated simply as ‘slum’ or ‘shantytown’, but these terms connote negative characteristics such as shortage, poverty, and deprivation which end up stigmatizing these low income suburbs. Curta Favela (Favela Shorts) is an independent project in which all participants join to use photography and participatory audiovisual production as tools for social change and to raise consciousness. As cameras are not affordable for favela dwellers, Curta Favela’s volunteers teach favela residents how they can use their mobile phones and compact cameras to take pictures and make movies, and afterwards, how they can edit the data using free editing video software programs and publish it on the Internet. To record audio, they use their mp3 or mobile phones. The main aim of this study is to shed light not only on how this project operates, but also to highlight how collective intelligence can be used as a way of fighting against a lack of basic resources.

The use of CCTV to police public spaces : a case of big brother or big friend?

This paper considers the role of CCTV (closed circuit television) in the surveillance, policing and control of public space in urban and rural locations, specifically in relation to the use of public space by young people. The use of CCTV technology in public spaces is now an established and largely uncontested feature of everyday life in a number of countries and the assertion that they are essentially there for the protection of law abiding and consuming citizens has broadly gone unchallenged. With little or no debate in the U.K. to critique the claims made by the burgeoning security industry that CCTV protects people in the form of a ‘Big Friend’, the state at both central and local levels has endorsed the installation of CCTV apparatus across the nation. Some areas assert in their promotional material that the centre of the shopping and leisure zone is fully surveilled by cameras in order to reassure visitors that their personal safety is a matter of civic concern, with even small towns and villages expending monies on sophisticated and expensive to maintain camera systems. It is within a context of monitoring, recording and control procedures that young people’s use of public space is constructed as a threat to social order, in need of surveillance and exclusion which forms a major and contemporary feature in shaping thinking about urban and rural working class young people in the U.K. As Loader (1996) notes, young people’s claims on public space rarely gain legitimacy if ‘colliding’ with those of local residents, and Davis (1990) describes the increasing ‘militarization and destruction of public space’, while Jacobs (1965) asserts that full participation in the ‘daily life of urban streets’ is essential to the development of young people and beneficial for all who live in an area. This paper challenges the uncritical acceptance of widespread use of CCTV and identifies its oppressive and malevolent potential in forming a ‘surveillance gaze’ over young people (adapting Foucault’s ‘clinical gaze’c. 1973) which can jeopardise mental health and well being in coping with the ‘metropolis’, after Simmel, (1964).

Airborne collision scenario flight tests : impact of angle measurement errors on reactive vision-based avoidance control

The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.

Effects of average speed enforcement on speed compliance and crashes : a review of the literature

Average speed enforcement is a relatively new approach gaining popularity throughout Europe and Australia. This paper reviews the evidence regarding the impact of this approach on vehicle speeds, crashes rates and a number of additional road safety and public health outcomes. The economic and practical viability of the approach as a road safety countermeasure is also explored. A literature review, with an international scope, of both published and grey literature was conducted. There is a growing body of evidence to suggest a number of road safety benefits associated with average speed enforcement, including high rates of compliance with speed limits, reductions in average and 85th percentile speeds and reduced speed variability between vehicles. Moreover, the approach has been demonstrated to be particularly effective in reducing excessive speeding behaviour. Reductions in crash rates have also been reported in association with average speed enforcement, particularly in relation to fatal and serious injury crashes. In addition, the approach has been shown to improve traffic flow, reduce vehicle emissions and has also been associated with high levels of public acceptance. Average speed enforcement offers a greater network-wide approach to managing speeds that reduces the impact of time and distance halo effects associated with other automated speed enforcement approaches. Although comparatively expensive it represents a highly reliable approach to speed enforcement that produces considerable returns on investment through reduced social and economic costs associated with crashes.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

Featureless visual processing for SLAM in changing outdoor environments

Vision-based SLAM is mostly a solved problem providing clear, sharp images can be obtained. However, in outdoor environments a number of factors such as rough terrain, high speeds and hardware limitations can result in these conditions not being met. High speed transit on rough terrain can lead to image blur and under/over exposure, problems that cannot easily be dealt with using low cost hardware. Furthermore, recently there has been a growth in interest in lifelong autonomy for robots, which brings with it the challenge in outdoor environments of dealing with a moving sun and lack of constant artificial lighting. In this paper, we present a lightweight approach to visual localization and visual odometry that addresses the challenges posed by perceptual change and low cost cameras. The approach combines low resolution imagery with the SLAM algorithm, RatSLAM. We test the system using a cheap consumer camera mounted on a small vehicle in a mixed urban and vegetated environment, at times ranging from dawn to dusk and in conditions ranging from sunny weather to rain. We first show that the system is able to provide reliable mapping and recall over the course of the day and incrementally incorporate new visual scenes from different times into an existing map. We then restrict the system to only learning visual scenes at one time of day, and show that the system is still able to localize and map at other times of day. The results demonstrate the viability of the approach in situations where image quality is poor and environmental or hardware factors preclude the use of visual features.

Long summer days : grounded learning of words for the uneven cycles of real world events

Time and space are fundamental to human language and embodied cognition. In our early work we investigated how Lingodroids, robots with the ability to build their own maps, could evolve their own geopersonal spatial language. In subsequent studies we extended the framework developed for learning spatial concepts and words to learning temporal intervals. This paper considers a new aspect of time, the naming of concepts like morning, afternoon, dawn, and dusk, which are events that are part of day-night cycles, but are not defined by specific time points on a clock. Grounding of such terms refers to events and features of the diurnal cycle, such as light levels. We studied event-based time in which robots experienced day-night cycles that varied with the seasons throughout a year. Then we used meet-at tasks to demonstrate that the words learned were grounded, where the times to meet were morning and afternoon, rather than specific clock times. The studies show how words and concepts for a novel aspect of cyclic time can be grounded through experience with events rather than by times as measured by clocks or calendars

Measurement error of rearfoot kinematics during running between a 100Hz and 30Hz camera

Background: Measurement accuracy is critical for biomechanical gait assessment. Very few studies have determined the accuracy of common clinical rearfoot variables between cameras with different collection frequencies. Research question: What is the measurement error for common rearfoot gait parameters when using a standard 30Hz digital camera compared to 100Hz camera? Type of study: Descriptive. Methods: 100 footfalls were recorded from 10 subjects ( 10 footfalls per subject) running on a treadmill at 2.68m/s. A high-speed digital timer, accurate within 1ms served as an external reference. Markers were placed along the vertical axis of the heel counter and the long axis of the shank. 2D coordinates for the four markers were determined from heel strike to heel lift. Variables of interest included time of heel strike (THS), time of heel lift (THL), time to maximum eversion (TMax), and maximum rearfoot eversion angle (EvMax). Results: THS difference was 29.77ms (+/- 8.77), THL difference was 35.64ms (+/- 6.85), and TMax difference was 16.50ms (+/- 2.54). These temporal values represent a difference equal to 11.9%, 14.3%, and 6.6% of the stance phase of running gait, respectively. EvMax difference was 1.02 degrees (+/- 0.46). Conclusions: A 30Hz camera is accurate, compared to a high-frequency camera, in determining TMax and EvMax during a clinical gait analysis. However, relatively large differences, in excess of 12% of the stance phase of gait, for THS and THL variables were measured.

Media and information literacy at Queensland University of Technology and in Australia

Media and Information Literacy is the focus of several teaching and research projects at Queensland University of Technology and there is particular emphasis placed on digital technologies and how they are used for communication, information use and learning in formal contexts such as schools. Research projects are currently taking place in several locations where investigators are collecting data on approaches to the use of digital media tools like cameras and editing systems, tablet computers and video games. This complements QUT’s teacher preparation courses, including preparation to implement UNESCO’s Online Course in Media and Information Literacy and Intercultural Dialogue in 2013. This work takes place in the context of projects occurring at the National level in Australia that continue to promote Media and Information Literacy.

Vision based control for micro aerial vehicles : Application to sense and avoid

This work presents a collision avoidance approach based on omnidirectional cameras that does not require the estimation of range between two platforms to resolve a collision encounter. Our method achieves minimum separation between the two vehicles involved by maximising the view-angle given by the omnidirectional sensor. Only visual information is used to achieve avoidance under a bearing- only visual servoing approach. We provide theoretical problem formulation, as well as results from real flights using small quadrotors

Online calibration of stereo rigs for long-term autonomy

Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods. This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework. We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.