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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jalalian, A. Chalup, S.K. Ostwald, M.J. |
| Copyright Year | 2010 |
| Description | Author affiliation: School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan 2308, Australia (Jalalian, A.; Chalup, S.K.) || School of Architecture and Built Environment, The University of Newcastle, Callaghan 2308, Australia (Ostwald, M.J.) |
| Abstract | 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. |
| Starting Page | 442 |
| Ending Page | 447 |
| File Size | 1241253 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424463343 |
| e-ISBN | 9781424463374 |
| DOI | 10.1109/IWACI.2010.5585134 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Analytical models Urban areas Hidden Markov models Humans Support vector machine classification Trajectory |
| Content Type | Text |
| Resource Type | Article |
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