Video-Based Motion Capture for Measuring Human Movement

Through the advancement of electronics technologies, human motion analysis applications span many domains. Existing commercially available magnetic, mechanical and optical systems for motion capture and analyses are far from being able to operate in natural scenarios and environments. The current shortcoming of requiring the subject to wear sensors and markers on the body has prompted development directed towards a marker-less setup using computer vision approaches. However, there are still many challenges and problems in computer vision methods such as inconsistency of illumination, occlusion and lack of understanding and representation of its operating scenario. The authors present a videobased marker-less motion capture method that has the potential to operate in natural scenarios such as occlusive and cluttered scenes. In specific applications in sports biomechanics and education, which are stimulated by the usage of interactive digital media and augmented reality, accurate and reliable capture of human motion are essential.

A Framework for Data Warehousing and Mining in Sensor Stream Application Domains

The recent advances in sensor technologies have made these small, tiny devices much cheaper and convenient to use in many different applications, for example, the weather and environmental monitoring applications, the hospital and factory operation sites, sensor devices on the traffic road and moving vehicles and so on. The data collected from sensors forms a sensor stream and is transferred to the server to perform data warehousing and mining tasks for the end user to perform data analysis. Several data preprocessing steps are necessary to enrich the data with domain information for the data warehousing and mining tasks in the sensor stream applications. This chapter presents a general framework for domain-driven mining of sensor stream applications. The proposed framework is able to enrich sensor streams with additional domain information that meets the application requirements. Experimental studies of the proposed framework are performed on real data for two applications: a traffic management and an environmental monitoring site.

Modelling Pedestrian Movement to Measure On-Street Crime Risk

This chapter presents results for the first large-scale analysis of street crime rates that utilizes accurate on-street pedestrian population estimates. Pedestrian counts were generated at the street segment level for an area in central London (UK) using a modeling process that utilized key indicators of pedestrian movement and sample observations. Geocoded street crime positioned on street segments then allowed for street crime rates to be calculated for the entire central London study area’s street network. These street crime rate measures were then compared against street crime volume patterns (e.g., hotspot maps of street crime density) and street crime rate statistics and maps that were generated from using the residential population as the denominator. The research demonstrates the utility of pedestrian modeling for generating better and more realistic measures for street crime rates, suggesting that if the residential population is used as a denominator for local level street crime analysis it may only misinform and mislead the interpretation and understanding of on- to pedestrians. The research also highlights the importance of crime rate analysis for understanding and explaining crime patterns, and suggests that with accurate analysis of crime rates, policing, and crime prevention initiatives can be improved.

Navigating a Speckled World

The Speckled Computing project is a large multisite research project based in Scotland, UK. The aim of the project is to investigate, prototype, and produce tiny (1mm3) computational devices, called Specks, that can be configured into wireless sensor networks, called SpeckNets. Our particular interest is in how people might interact in such environments, what interaction tools they require, and what characteristics are required to be provided by the operating system of the Specks. Interaction in these environments places the human physically inside an information space. At one time, the human may be interacting with one Speck, at another with a hundred, and at another with several thousand. Moreover, the Specks themselves have no input method, apart from their sensors, and no output display. We explore these issues through taking some theories of distributed information spaces, some design principles from information visualization, and report on some empirical studies of prototypes and simulations that have been developed.

Law and Technology

In this chapter the authors analyze the concept and definitions of anonymity in the modern connected world. In particular, they explore if modern technology renders complete anonymity impossible and if a new definition of anonymity needs to be adopted. They examine examples of anonymous use of technology that illustrate the complexity of the concept of anonymity and demonstrate that access to anonymity is not uniform for data owners with regard to multiple data controllers and audiences in complex systems and processes. They evaluate legal definitions of “anonymity” and “anonymous data” as well as the right to anonymity provided in the European directives and by some European statutes, observing that anonymity cannot be absolute, that only “relative” anonymity is realistic in the present technological environment, and that different degrees of anonymity exist. They address the issue of measuring these degrees or levels of anonymity in complex systems, in order to provide a new foundation for a nuanced and comprehensive understanding of anonymity. The authors conclude that the concept of relative anonymity can become the basis for a new and more effective approach to personal data protection.

Show Me My Way

The growing amount of ubiquitously available location based information offers great chances for the development of mobile pedestrian navigation services. Yet, providing spot-on real-time adequate information remains challenging, as relevant information needs to be filtered and group-related behaviour patterns and preferences are still insufficiently known. In this chapter, the authors focus on two aspects. Firstly, they consider the issue of how to comprehensively investigate human spatio-temporal behaviour patterns in order to enable the provision of customised navigation information, and secondly, they discuss potential impacts of ubiquitous wayfinding systems on human perception of space and possible resulting navigation behaviour modifications.

Attribute Hierarchies to Tally Fish

This chapter presents a model that addresses some shortcomings associated with limitations in the way that electronic identities are used in an application environment. This model, Snowflake, allows the exchange of validation data in order to establish trust when identity attributes are used in applications. Snowflake leverages upon groups of validation authorities as electronic intermediaries to facilitate application interoperation. The application area of choice is the electronic reporting of fish catches by a vessel’s master in line with the European Union legal framework. Grouping together the services of multiple validation authorities maximises the utilisation of resources available especially in environments that do not shy out in sharing resources and data such and the electronic fish logbook provides a good platform in this respect.

FriendFreight

The relatively new ability to rapidly transfer digital information to people as they move through cities opens up exciting possibilities for services that alleviate some of the issues that dense urban centers face. This chapter examines the potential for one such service – named FriendFreight – to reduce some of the negative effects of goods transportation in cities. FriendFreight operates through exploiting the real-time location information of people and goods and the ability for members of a community to deliver items for others while moving through the city themselves. It aims to lower the number of ‘unnecessary trips’ that people make to obtain some small goods - groceries, books, documents and dry-cleaning - and reduce what we define as travel demand in the city. However, the success of such a service relies not only on accessing real time location information but also on an understanding of how and why people might deliver goods for each other. Thus, this chapter explores two things: how incentives, trust and reciprocity can be built in services that harness digital information; and how the feasibility of a service like FriendFreight can be established given a particular real world context - Copenhagen and bicycles. Through this, the authors show that access to real-time location and movement information can open up innovative ways of tackling problems in cities from the ‘bottom-up’ but that essential to this is the nurturing of trust between users of the service. They also demonstrate that it is possible to achieve a significant reduction in travel demand through using FriendFreight for certain types of goods in the context of Copenhagen.

Revealing Taxi Driver's Mobility Intelligence through His Trace

This study develops a methodology for the analysis of taxi drivers’ operation behavior in a real urban environment. The research objective is to spatially and temporally quantify, visualize, and examine taxi drivers’ operational behavior and skill (as measured by income), which the authors call ‘mobility intelligence’. For the first time, taxi drivers’ different operation strategies were systematically analyzed through their daily activity traces. Routes and economic behavior data were collected with the use of Global Positioning System (GPS) and a set of spatiotemporal analysis tools were developed. Drivers are categorized by their daily income into top drivers and ordinary drivers. A 3D clustering technique is used to quantitatively analyze the spatiotemporal patterns for top driver and ordinary driver. Also, fractal analysis is employed to quantify tortuosity of movement paths and to explore how top and ordinary drivers operate on different spatial scales at different times, where the primary focus is to reveal top driver mobility intelligence.

Setting the Stage for the Integration of Demand Responsive Transport and Location-Based Services

Demand responsive transport systems such as paratransit could deliver services that collective transport simply cannot provide. Location-based services may be capable of bridging the divide between transport services without fixed routes, stops or schedules and their potential users. This chapter outlines how the integration of demand responsive transport and location-based services may help to deliver a flexible transport system that is sensitive to the needs of individual users in urban and rural areas. Such a system would have the potential to liberate urbanism from the need to orient spatial development on rigid transit lines.