Abstract:
This paper proposes a new approach for trajectory clustering and visualization. During clustering, speed and direction are both taken into account as the important proper...Show MoreMetadata
Abstract:
This paper proposes a new approach for trajectory clustering and visualization. During clustering, speed and direction are both taken into account as the important properties of a trajectory. Additionally, the temporal change of the trajectories is explicitly considered in the procedure of clustering. Importantly, we introduce the uncertainty to represent the homogeneity of the updating trajectories based on their speed and direction attributes, to help observe and understand the happening of the trajectory data. Finally, based on the use of the HSV color space, we devise three patterns for graphically presenting the trajectory data in different perspectives. Namely, 'H+S' visualizes the clustered trajectories emphasizing the speed attribute of them. 'H+S+Update' depicts more information on the "latest" trajectory data, compared with the results by 'H+S'. 'H+V+Update' explicitly presents the uncertainty of the trajectory data. Our approach has shown its potential for the effective trajectory analysis.
Date of Conference: 16-18 July 2014
Date Added to IEEE Xplore: 22 September 2014
Electronic ISBN:978-1-4799-4103-2
ISSN Information:
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- IEEE Keywords
- Index Terms
- Color Space ,
- Trajectory Data ,
- Clustering Procedure ,
- Trajectory Clustering ,
- Hierarchical Clustering ,
- Clustering Algorithm ,
- Density Estimation ,
- Pedestrian ,
- Grid Cells ,
- Intersection Point ,
- Anomaly Detection ,
- Cluster Representatives ,
- Uncertainty Information ,
- Upper Area ,
- Yellow Area ,
- Clustering Visualization ,
- Speed Information ,
- Bottom Area ,
- Trajectory Segments ,
- Track Segment
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Color Space ,
- Trajectory Data ,
- Clustering Procedure ,
- Trajectory Clustering ,
- Hierarchical Clustering ,
- Clustering Algorithm ,
- Density Estimation ,
- Pedestrian ,
- Grid Cells ,
- Intersection Point ,
- Anomaly Detection ,
- Cluster Representatives ,
- Uncertainty Information ,
- Upper Area ,
- Yellow Area ,
- Clustering Visualization ,
- Speed Information ,
- Bottom Area ,
- Trajectory Segments ,
- Track Segment
- Author Keywords