Seq2Seq 오토인코더 기반의 이상 이동경로 탐지

Abstract

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.