Motion recovery for video content classification
ACM Transactions on Information Systems (TOIS) - Special issue on video information retrieval
Scaling up dynamic time warping for datamining applications
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Spatio-temporal representation and retrieval using moving object's trajectories
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
The Journal of Machine Learning Research
Mean Shift Based Clustering in High Dimensions: A Texture Classification Example
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Variational methods for the Dirichlet process
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Symbolic representation and retrieval of moving object trajectories
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
A hybrid system for affine-invariant trajectory retrieval
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Discovering Objects and their Localization in Images
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Bi-Directional Tracking Using Trajectory Segment Analysis
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Motion Trajectory Learning in the DFT-Coefficient Feature Space
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Indexing Multidimensional Time-Series
The VLDB Journal — The International Journal on Very Large Data Bases
Using Dependent Regions for Object Categorization in a Generative Framework
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Comparison of Similarity Measures for Trajectory Clustering in Outdoor Surveillance Scenes
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Trend Analysis for Large Document Streams
ICMLA '06 Proceedings of the 5th International Conference on Machine Learning and Applications
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
International Journal of Computer Vision
An HDP-HMM for systems with state persistence
Proceedings of the 25th international conference on Machine learning
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
Probabilistic Modeling of Scene Dynamics for Applications in Visual Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Event analysis based on multiple interactive motion trajectories
IEEE Transactions on Circuits and Systems for Video Technology
Syntactic matching of trajectories for ambient intelligence applications
IEEE Transactions on Multimedia
Learning to recognize video-based spatiotemporal events
IEEE Transactions on Intelligent Transportation Systems
International Journal of Computer Vision
Spatio-temporal descriptor using 3D curvature scale space
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Clustering of vehicle trajectories
IEEE Transactions on Intelligent Transportation Systems
Discovering clusters in motion time-series data
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Subtrajectory-based video indexing and retrieval
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Learning semantic scene models by trajectory analysis
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
IEEE Transactions on Intelligent Transportation Systems
Real-Time Motion Trajectory-Based Indexing and Retrieval of Video Sequences
IEEE Transactions on Multimedia
Motion-based video retrieval by trajectory matching
IEEE Transactions on Circuits and Systems for Video Technology
A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance
IEEE Transactions on Circuits and Systems for Video Technology
Event Detection Using Trajectory Clustering and 4-D Histograms
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
In this paper, we propose a hierarchical Bayesian model, an improved hierarchical Dirichlet process-hidden Markov model (iHDP-HMM), for visual document analysis. The iHDP-HMM is capable of clustering visual documents and capturing the temporal correlations between the visual words within a visual document while identifying the number of document clusters and the number of visual topics adaptively. A Bayesian inference mechanism for the iHDP-HMM is developed to carry out likelihood evaluation, topic estimation, and cluster membership prediction. We apply the iHDP-HMM to simultaneously cluster motion trajectories and discover latent topics for trajectory words, based on the proposed method for constructing the trajectory word codebook. Then, an iHDP-HMM-based probabilistic trajectory retrieval framework is developed. The experimental results verify the clustering accuracy of the iHDP-HMM and trajectory retrieval accuracy of the proposed framework.