Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
On Computing Metric Upgrades of Projective Reconstructions Under the Rectangular Pixel Assumption
SMILE '00 Revised Papers from Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments
Shape-Based Similarity Query for Trajectory of Mobile Objects
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
Similarity Search for Multidimensional Data Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Efficient Searches for Similar Subsequences of Different Lengths in Sequence Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A Multi-Object Tracking System for Surveillance Video Analysis
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Motion Trajectory Learning in the DFT-Coefficient Feature Space
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Comparison of Similarity Measures for Trajectory Clustering in Outdoor Surveillance Scenes
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Experimental comparison of representation methods and distance measures for time series data
Data Mining and Knowledge Discovery
TODMIS: mining communities from trajectories
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
| Hi-index | 0.00 |
The problem of trajectory similarity has been recently attracted research interest considerably, due to its importance in diverse fields. In this work, we study trajectory similarity by attacking the problem taking an information retrieval perspective. Trajectories are first decomposed by using a grid and each trajectory is mapped to a multidimensional space where Latent Semantic Analysis is applied. Distance measures like Euclidean distance or cosine distance are applied to process similarity queries (range queries, k-NN queries). Performance evaluation results, based on real-life data sets, show the simplicity and effectiveness of the proposed scheme.