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Online handwriting trajectory reconstruction from kinematic sensors using temporal convolutional network
Handwriting with digital pens is a common way to facilitate human–computer interaction through the use of online handwriting (OH) trajectory...
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SGAMTE-Net: A pedestrian trajectory prediction network based on spatiotemporal graph attention and multimodal trajectory endpoints
Predicting pedestrians' future trajectories is crucial in fields like autonomous driving and robotics. Pedestrian behavior is influenced by...
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Sub-trajectory clustering with deep reinforcement learning
Sub-trajectory clustering is a fundamental problem in many trajectory applications. Existing approaches usually divide the clustering procedure into...
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SimiDTR: Deep Trajectory Recovery with Enhanced Trajectory Similarity
The pervasiveness of GPS-equipped smart devices and the accompanying deployment of sensing technologies generates increasingly massive amounts of...
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Reactive buffering window trajectory segmentation: RBW-TS
Mobility data of a moving object, called trajectory data, are continuously generated by vessel navigation systems, wearable devices, and drones, to...
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Rotation invariant GPS trajectory mining
Mining of GPS trajectories of moving vehicles and devices can provide valuable insights into urban systems, planning and operational applications....
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Vision-Based Mobile Robots Control Along a Given Trajectory
The paper presents the application of a computer vision approach to tracking the mobile robot’s state. As an exemplary environment, we use a feedback...
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TULRN: Trajectory user linking on road networks
Linking trajectories to users who generate them with deep learning techniques has been a popular research topic in recent years, due to the...
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SAMLink: a mobility signature augmentation model for trajectory-user linking
Trajectory-user linking (TUL) aims to link trajectories to users who generate them, based on the historical trajectories of a set of users (e.g.,...
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Low-cost and high-performance abnormal trajectory detection based on the GRU model with deep spatiotemporal sequence analysis in cloud computing
Trajectory anomalies serve as early indicators of potential issues and frequently provide valuable insights into event occurrence. Existing methods...
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Comparison of Geospatial Trajectory Clustering and Feature Trajectory Clustering for Public Transportation Trip Data
One of the techniques for the analysis of travel patterns on a public transport network is the clustering of the users movements, in order to...
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Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
Situation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement...
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Efficient Mining of Volunteered Trajectory Datasets
With the ubiquity of mobile devices that are capable of tracking positions (be it via GPS or Wi-Fi/mobile network localization), there is a...
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Rugby Ball Detection, Tracking and Future Trajectory Prediction Algorithm
This paper presents a custom object detection and tracking algorithm for position estimation and trajectory prediction of a moving rugby ball. The...
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An A2-Gurobi algorithm for route recommendation with big taxi trajectory data
To address the problems of high fuel consumption and severe traffic congestion caused by blindly cruising, we propose a Gurobi optimization algorithm...
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Dummy trajectory generation scheme based on generative adversarial networks
Dummy trajectory is widely used to protect the privacy of mobile users’ locations. However, two main challenges remain: (1) Map background...
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Spatio-temporal trajectory data modeling for fishing gear classification
International Organizations urge the protection of our oceans and their ecosystems due to their immeasurable importance to humankind. Since illegal...
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Transformer based composite network for autonomous driving trajectory prediction on multi-lane highways
In order to navigate through complex traffic scenarios safely and efficiently, the autonomous vehicle (AV) predicts its own behavior and future...
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Efficient Trajectory Clustering of Movements of Moving Objects
Trajectory data mining is a very important data mining technique with respect to clustering of moving objects trajectories. It is the latest and hot...
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A Novel Approach to Trajectory Situation Awareness Using Multi-modal Deep Learning Models
This paper presents a novel multi-modal deep learning framework, TSA-MM, for accurate trajectory situational awareness in transportation and military...