Seq2Seq 오토인코더 기반의 이상 이동경로 탐지Anomalous Trajectory Detection Based on Seq2Seq Auto-Encoder

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RNN model has become a specialized model for time-series data by showing outstanding performance in various application fields that use the time-series data. However, unlike the common time-series data, the trajectory data is a spatio-temporal data that contains both spatial and temporal information so the trajectory data requires a specialized methodology for feature extraction that utilizes both spatial and temporal characteristics. Because simply constructing a RNN type model is insufficient for efficient feature extraction, we propose Seq2Seq Auto-Encoder based model that effectively captures distinctive high-quality features and movement characteristics from the trajectories. Our proposed Seq2Seq Auto-Encoder based model to extract complicated movement features and use extracted feature vectors to detect outlying trajectories.
Publisher
대한공간정보학회
Issue Date
2020-03
Language
English
Citation

대한공간정보학회지, v.28, no.1, pp.35 - 40

ISSN
1598-2955
DOI
10.7319/kogsis.2020.28.1.035
URI
http://hdl.handle.net/10203/277310
Appears in Collection
CS-Journal Papers(저널논문)
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