http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11631 Research Doctorate - Doctor of Philosophy (PhD) 2012-10-15T02:50:07.845Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10070 This paper proposes a new method for pedestrian behaviour analysis in simulated urban environments. Our proposed software system analyses pedestrian behaviour with a combined focus on movement trajectories, walking speed and the angle between the movement vector and gaze vector of individuals in large groups of simulated pedestrians. The system learns a statistical model characterising normal behaviour, based on sample observations of regular pedestrian movements without the impact of significant visual attractions in the environment. Sudden changes of the pedestrians’ behavioural characteristics, caused by the visual detection of “attractive” objects, are considered as abnormal behaviour. The simulated environment, which is at the core of the research can be automatically generated using scanned line drawings of two-dimensional street maps or public spaces. In the simulation model a variety of scenarios can be defined and modified by altering different parameters. Using the example of Wheeler Place in Newcastle (Australia) our pilot experiments demonstrate how pedestrian behaviour characteristics can depend on selected abstract features in urban space. The purpose of the system is to support architects and urban designers to better assess the impact of pedestrian behaviour on planned urban spaces and streetscapes. 2012-09-17T05:44:43.114Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10764 The purpose of the software system described in this article is to support architects and urban designers to better assess the impact of pedestrian behaviour on planned urban spaces and streetscapes. A new method for modelling and simulating pedestrians in urban environments is proposed. It analyses pedestrian behaviour with a combined focus on movement trajectories, walking speed and the angle between the movement vector and the gaze vector of individuals in large groups of simulated pedestrians. The system learns a statistical model characterizing normal behaviour, based on sample observations of regular pedestrian movements without the impact of significant visual attractions in the environment. Sudden changes of the pedestrians' behavioural characteristics, caused by the visual detection of ‘attractive’ objects, are considered as abnormal behaviour. The simulated environment can be automatically generated using scanned line drawings of two-dimensional street maps or public spaces. In the simulation model, a variety of scenarios can be defined and modified by altering different parameters. Using the example of Wheeler Place in Newcastle (Australia), our pilot experiments demonstrate how pedestrian behaviour characteristics can depend on selected abstract features in urban space. Among 10 different example scenarios, the analyser was able to identify the most frequently visited positions associated with attractive objects. 2012-05-08T02:30:02.509Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:10064 This study describes a new approach for pedestrian behaviour analysis in simulated urban environments. A software system was developed to analyse the dynamics of pedestrians with a focus on their movement trajectories and the angle between the pedestrian's movement vector and their gaze vector. One-class support vector machines and dynamic time warping were applied for outlier detection in order to indentify noticeable changes in the visual behavior of individuals in a group of simulated pedestrians who walk past visually attractive objects. Results of simulation experiments demonstrate how different pedestrian behaviour characteristics can be detected and distinguished in a variety of abstract urban design scenarios. The described software system was designed to allow future real world applications by feeding video recordings of real pedestrians into the model. 2012-02-16T01:40:05.926Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9506 Improving our capacity to measure the sightlines and paths of pedestrians can assist with our understanding of complex spatial environments, which can in turn lead to improvements in urban design. However, in practice, the gaze direction of pedestrians is difficult to estimate due to high noise levels in video recordings coupled with the subtlety of gaze dynamics. In this paper robots are used to develop a pedestrian gaze analysis system that is suitable for urban environments. The present paper describes a model street scene that was set up within a laboratory where autonomous humanoid robots of approximately 55cm in height were programmed to model the behaviour of human pedestrians. Experiments were conducted to collect a variety of data from overhead cameras, video cameras, and from the robot’s view through its internal camera as it traversed the model street, where it could become distracted by “visually attractive objects”. Overhead recordings were processed to obtain distracted and undistracted gaze signals which were analysed after filtering. Pilot experiments were performed for extracting 3D gaze vectors from video sequences using a manifold learning approach. An outline of the temporal behaviour analysis technique used on the obtained signals is also presented. This approach aims to improve the precision of pedestrian gaze analysis in real urban environments. 2012-01-30T05:12:06.492Z ]]>