Parking, parties and pets : disputes - the dark side of community living

In the last decade community living, in master planned communities or strata titled complexes, has increased. As land becomes scarcer, the popularity of these schemes is predicted to grow. Offsetting this popularity is the peculiarities of community living, in particular the often unthought-of difficulties arising from living in very close proximity to your neighbour. Such difficulties affect both amenity of life and property value. This paper seeks to inform practitioners of the issues arising from community living. It does this by identifying the more common forms of disputes and considering recent tribunal and court decisions. The paper concludes by identifying the dispute warning signs to assist to practitioners with the valuation process.

Pets join the family and business is booming

The recently proposed $338 million merger of Australian vet and pet products companies Greencross and Petbarn illustrates something that perhaps we have known for a while now: our pets are becoming more important to us than ever before. Pets are no longer viewed simply as animals, but have become “humanised” to the point that they are considered by many to be members of the family. Indeed, nearly 90% of Australians polled in a recent survey said they thought of their dog or cat as a member of the family, and even admitted to treating them better than human family members, which has a substantial impact on purchasing behaviours...

Soft-biometrics : unconstrained authentication in a surveillance environment

Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. These include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics (i.e. face, voice) which require cooperation from the subject, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. Whilst these traits cannot provide robust authentication, they can be used to provide coarse authentication or identification at long range, locate a subject who has been previously seen or who matches a description, as well as aid in object tracking. In this paper we propose three part (head, torso, legs) height and colour soft biometric models, and demonstrate their verification performance on a subset of the PETS 2006 database. We show that these models, whilst not as accurate as traditional biometrics, can still achieve acceptable rates of accuracy in situations where traditional biometrics cannot be applied.

Designing locative and social media technologies for community collaboration and social benefit : PetSearch

The convergence of locative and social media with collaborative interfaces and data visualisation has expanded the potential of online information provision. Offering new ways for communities to share contextually specific information, it presents the opportunity to expand social media’s current focus on micro self-publishing with applications that support communities to actively address areas of local need. This paper details the design and development of a prototype application that illustrates this potential. Entitled PetSearch, it was designed in collaboration with the Animal Welfare League of Queensland to support communities to map and locate lost, found and injured pets, and to build community engagement in animal welfare issues. We argue that, while established approaches to social and locative media provide a useful foundation for designing applications to harness social capital, they must be re-envisaged if they are to effectively facilitate community collaboration. We conclude by arguing that the principles of user engagement and co-operation employed in this project can be extrapolated to other online approaches that aim to facilitate co-operative problem solving for social benefit.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Animal stories : flash flood 2011

Flash flood disasters happen suddenly. The Toowoomba Lockyer Valley flash flood in January 2011 was not forecast by the Bureau of Meteorology until after it had occurred. Domestic and wild animals gave the first warning of the disaster in the days leading up to the event and large animals gave warnings on the morning of the disaster. Twenty-three people, including 5 children in the disaster zone died. More than 500 people were listed as missing. Some of those who died, perished because they stayed in the disaster zone to look after their animals while other members of their family escaped to safety. Some people who were in danger refused to be rescued because they could not take their pets with them. During a year spent recording accounts of the survivors of the disaster, animals were often mentioned by survivors. Despite the obvious perils, people risked their lives to save their animals; people saw animals try to save each other; animals rescued people; people rescued animals; animals survived where people died; animals were used to find human victims in the weeks after the disaster; and animals died. The stories of the flood present challenges for pet owners, farmers, counter disaster planners, weather forecasters and emergency responders in preparing for disasters, responding to them and recovering after them.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

The pet factor - Companion animals as a conduit for getting to know people, friendship formation and social support

BACKGROUND: While companion animals have been previously identified as a direct source of companionship and support to their owners, their role as a catalyst for friendship formation or social support networks among humans has received little attention. This study investigated the indirect role of pets as facilitators for three dimensions of social relatedness; getting to know people, friendship formation and social support networks. METHODS: A telephone survey of randomly selected residents in four cities, one in Australia (Perth; n = 704) and three in the U.S. (San Diego, n = 690; Portland, n = 634; Nashville, n = 664) was conducted. All participants were asked about getting to know people within their neighborhood. Pet owners were asked additional questions about the type/s of pet/s they owned, whether they had formed friendships as a result of their pet, and if they had received any of four different types of social support from the people they met through their pet. RESULTS: Pet owners were significantly more likely to get to know people in their neighborhood than non-pet owners (OR 1.61; 95%CI: 1.30, 1.99). When analyzed by site, this relationship was significant for Perth, San Diego and Nashville. Among pet owners, dog owners in the three U.S. cities (but not Perth) were significantly more likely than owners of other types of pets to regard people whom they met through their pet as a friend (OR 2.59; 95%CI: 1.94, 3.46). Around 40% of pet owners reported receiving one or more types of social support (i.e. emotional, informational, appraisal, instrumental) via people they met through their pet. CONCLUSION: This research suggests companion animals can be a catalyst for several dimensions of human social relationships in neighborhood settings, ranging from incidental social interaction and getting to know people, through to formation of new friendships. For many pet owners, their pets also facilitated relationships from which they derived tangible forms of social support, both of a practical and emotionally supportive nature. Given growing evidence for social isolation as a risk factor for mental health, and, conversely, friendships and social support as protective factors for individual and community well-being, pets may be an important factor in developing healthy neighborhoods.

Gap acceptance behavior of mobile phone distracted drivers at roundabouts

While mobile phones have become ubiquitous in modern society, the use of mobile phones while driving is increasing at an alarming rate despite the associated crash risks. A significant safety concern is that driving while distracted by a mobile phone is more prevalent among young drivers, a less experienced driving cohort with elevated crash risk. The objective of this study was to examine the gap acceptance behavior of distracted young drivers at roundabouts. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated gap acceptance scenario at roundabouts. Conflicting traffic from the right approach of a four-legged roundabout were programmed to have a series of vehicles having the gaps between them proportionately increased from two to six seconds. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. Results show that distracted drivers started responding to the gap acceptance scenario at a distance closer to the roundabout and approached the roundabout at slower speeds. They also decelerated at faster rates to reduce their speeds prior to gap acceptance compared to non-distracted drivers. Although accepted gap sizes were not significantly different across phone conditions, differences in the safety margins at various gap sizes—measured by Post Encroachment Time (PET) between the driven vehicle and the conflicting vehicle—were statistically significant across phone conditions. PETs for distracted drivers were smaller across different gap sizes, suggesting a lower safety margin taken by distracted drivers compared to non-distracted drivers. The results aid in understanding how cognitive distraction resulting from mobile phone conversations while driving influences driving behavior during gap acceptance at roundabouts.