Trajectory-Based Scene Understanding Using Dirichlet Process Mixture Model
Autor: | Partha Pratim Roy, Debi Prosad Dogra, Kelathodi Kumaran Santhosh, Bidyut B. Chaudhuri |
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Rok vydání: | 2021 |
Předmět: |
Computer science
Control (management) Nonparametric statistics 02 engineering and technology Mixture model computer.software_genre Computer Science Applications Data modeling Human-Computer Interaction Vehicle dynamics Control and Systems Engineering Gravity model of trade 020204 information systems 0202 electrical engineering electronic engineering information engineering Trajectory Data mining Electrical and Electronic Engineering Cluster analysis computer Software Information Systems |
Zdroj: | IEEE Transactions on Cybernetics. 51:4148-4161 |
ISSN: | 2168-2275 2168-2267 |
Popis: | Appropriate modeling of a surveillance scene is essential for the detection of anomalies in road traffic. Learning usual paths can provide valuable insight into road traffic conditions and thus can help in identifying unusual routes taken by commuters/vehicles. If usual traffic paths are learned in a nonparametric way, manual interventions in road marking can be avoided. In this paper, we propose an unsupervised and nonparametric method to learn the frequently used paths from the tracks of moving objects in $\Theta (kn)$ time, where $k$ denotes the number of paths and $n$ represents the number of tracks. In the proposed method, temporal dependencies of the moving objects are considered to make the clustering meaningful using temporally incremental gravity model (TIGM). In addition, the distance-based scene learning makes it intuitive to estimate the model parameters. Further, we have extended the TIGM hierarchically as a dynamically evolving model (DEM) to represent notable traffic dynamics of a scene. The experimental validation reveals that the proposed method can learn a scene quickly without prior knowledge about the number of paths ( $k$ ). We have compared the results with various state-of-the-art methods. We have also highlighted the advantages of the proposed method over the existing techniques popularly used for designing traffic monitoring applications. It can be used for administrative decision making to control traffic at junctions or crowded places and generate alarm signals, if necessary. |
Databáze: | OpenAIRE |
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