A Novel Online Trajectory Compression Algorithm for Real-time Trajectory Surveillance Applications

Real-time trajectory surveillance applications require displaying and updating of large-scale trajectory data streams in time. To achieve such a requirement, we proposed an online trajectory compression algorithm based on pyramid structured hierarchical grid coordinates and improved Sliding Window a...

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Bibliographic Details
Published in:2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) pp. 995 - 999
Main Authors: Li, Lin, Xia, Xuezhi, Xiong, Ziqian
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2019
Subjects:
Clustering algorithms
Compression algorithms
Computational complexity
Data visualization
grid coordinates
Information management
large-scale trajectory surveillance
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online trajectory compression
Real-time systems
Surveillance
Trajectory
trajectory big data
Uncertainty
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Summary:Real-time trajectory surveillance applications require displaying and updating of large-scale trajectory data streams in time. To achieve such a requirement, we proposed an online trajectory compression algorithm based on pyramid structured hierarchical grid coordinates and improved Sliding Window algorithm. According to the map scale of GIS system for displaying, we projected the original trajectory stream data points into the grid coordinates of the corresponding layer, and then applied the improved Sliding Window algorithm to generate the compressed trajectories. Furthermore, we generated the compressed trajectories corresponding to different map scales simultaneously as a cache data. The cached trajectory data will be directly loaded instead of the original data to improving the displaying efficiency when user changing the map scale. The experimental results show that the proposed algorithm can increase the loading speed of trajectory data to milliseconds on the basis of maintaining trajectory visualization effects at different map scales.
DOI:10.1109/IMCEC46724.2019.8983829