Trajectory Data Classification

This article comprehensively surveys the development of trajectory data classification. Considering the critical role of trajectory data classification in modern intelligent systems for surveillance security, abnormal behavior detection, crowd behavior analysis, and traffic control, trajectory data classification has attracted growing attention. According to the availability of manual labels, which is critical to the classification performances, the methods can be classified into three categories, i.e., unsupervised, semi-supervised, and supervised. Furthermore, classification methods are divided into some sub-categories according to what extracted features are used. We provide a holistic understanding and deep insight into three types of trajectory data classification methods and present some promising future directions.

[1]  Nikos Pelekis,et al.  On temporal-constrained sub-trajectory cluster analysis , 2017, Data Mining and Knowledge Discovery.

[2]  Mohan M. Trivedi,et al.  A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Michael G. Rabbat,et al.  GANC: Greedy Agglomerative Normalized Cut , 2011, ArXiv.

[4]  Sabine Timpf,et al.  Trajectory data mining: A review of methods and applications , 2016, J. Spatial Inf. Sci..

[5]  Philip S. Yu,et al.  Global distance-based segmentation of trajectories , 2006, KDD '06.

[6]  Imran N. Junejo,et al.  Social network model for crowd anomaly detection and localization , 2017, Pattern Recognit..

[7]  Jitendra Malik,et al.  Object Segmentation by Long Term Analysis of Point Trajectories , 2010, ECCV.

[8]  W. Eric L. Grimson,et al.  Learning Semantic Scene Models by Trajectory Analysis , 2006, ECCV.

[9]  Jun Gao,et al.  Learning universal multiview dictionary for human action recognition , 2017, Pattern Recognit..

[10]  Cordelia Schmid,et al.  Action recognition by dense trajectories , 2011, CVPR 2011.

[11]  Danica Kragic,et al.  Deep Representation Learning for Human Motion Prediction and Classification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Cláudio T. Silva,et al.  Vector Field k‐Means: Clustering Trajectories by Fitting Multiple Vector Fields , 2012, Comput. Graph. Forum.

[13]  Hassan Foroosh,et al.  Euclidean path modeling for video surveillance , 2008, Image Vis. Comput..

[14]  Stefano Spaccapietra,et al.  A Hybrid Model and Computing Platform for Spatio-semantic Trajectories , 2010, ESWC.

[15]  Christian S. Jensen,et al.  Discovery of convoys in trajectory databases , 2008, Proc. VLDB Endow..

[16]  Zhe Wang,et al.  Towards Good Practices for Very Deep Two-Stream ConvNets , 2015, ArXiv.

[17]  Dana Kulic,et al.  Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains , 2008, Int. J. Robotics Res..

[18]  Carol O'Sullivan,et al.  Globally Continuous and Non-Markovian Activity Analysis from Videos , 2016, ArXiv.

[19]  Christian S. Jensen,et al.  Effective Online Group Discovery in Trajectory Databases , 2013, IEEE Transactions on Knowledge and Data Engineering.

[20]  Shaogang Gong,et al.  Spectral clustering with eigenvector selection , 2008, Pattern Recognit..

[21]  Cordelia Schmid,et al.  Action Recognition with Improved Trajectories , 2013, 2013 IEEE International Conference on Computer Vision.

[22]  Jie Zhao,et al.  A review of moving object trajectory clustering algorithms , 2016, Artificial Intelligence Review.

[23]  Nicholas Jing Yuan,et al.  Approximate keyword search in semantic trajectory database , 2015, 2015 IEEE 31st International Conference on Data Engineering.

[24]  Wang-Chien Lee,et al.  Semantic trajectory mining for location prediction , 2011, GIS.

[25]  Zhouyu Fu,et al.  Semantic-Based Surveillance Video Retrieval , 2007, IEEE Transactions on Image Processing.

[26]  Yu Zheng,et al.  Trajectory Data Mining , 2015, ACM Trans. Intell. Syst. Technol..

[27]  Mohan M. Trivedi,et al.  Trajectory Learning for Activity Understanding: Unsupervised, Multilevel, and Long-Term Adaptive Approach , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Cordelia Schmid,et al.  Dense Trajectories and Motion Boundary Descriptors for Action Recognition , 2013, International Journal of Computer Vision.

[29]  Jinyang Chen,et al.  Clustering of trajectories based on Hausdorff distance , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[30]  Yu-Gang Jiang,et al.  Harnessing Object and Scene Semantics for Large-Scale Video Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[31]  Marios Hadjieleftheriou,et al.  Time relaxed spatiotemporal trajectory joins , 2005, GIS '05.

[32]  Shehzad Khalid,et al.  Motion Trajectory Learning in the DFT-Coefficient Feature Space , 2006, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06).

[33]  Takeo Kanade,et al.  Trajectory Space: A Dual Representation for Nonrigid Structure from Motion , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[34]  Jorge Dias,et al.  3D hand trajectory segmentation by curvatures and hand orientation for classification through a probabilistic approach , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[35]  Thomas Heinis,et al.  Efficient Mining of Regional Movement Patterns in Semantic Trajectories , 2017, Proc. VLDB Endow..

[36]  Limin Wang,et al.  Action recognition with trajectory-pooled deep-convolutional descriptors , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[37]  Jae-Gil Lee,et al.  TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering , 2008, Proc. VLDB Endow..

[38]  Hongdong Li,et al.  Spatial-Temporal Union of Subspaces for Multi-body Non-rigid Structure-from-Motion , 2017, ArXiv.

[39]  Nikos Pelekis,et al.  Clustering uncertain trajectories , 2011, Knowledge and Information Systems.

[40]  Yannis Manolopoulos,et al.  Trajectory Similarity Search in Spatial Networks , 2006, 2006 10th International Database Engineering and Applications Symposium (IDEAS'06).

[41]  Feng Xia,et al.  Big Trajectory Data: A Survey of Applications and Services , 2018, IEEE Access.

[42]  Thomas Brox,et al.  Motion Trajectory Segmentation via Minimum Cost Multicuts , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[43]  Xi Wang,et al.  Evaluating Two-Stream CNN for Video Classification , 2015, ICMR.

[44]  Di Wu,et al.  Application of trajectory clustering and regionalization to ocean eddies in the South China Sea , 2015, 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM).

[45]  Michael Dorr,et al.  Space-Variant Descriptor Sampling for Action Recognition Based on Saliency and Eye Movements , 2012, ECCV.

[46]  Wang-Chien Lee,et al.  Mining user similarity from semantic trajectories , 2010, LBSN '10.

[47]  Tiejun Huang,et al.  Sequential Deep Trajectory Descriptor for Action Recognition With Three-Stream CNN , 2016, IEEE Transactions on Multimedia.

[48]  Ickjai Lee,et al.  A Framework for Mining Semantic-Level Tourist Movement Behaviours from Geo-tagged Photos , 2016, Australasian Conference on Artificial Intelligence.

[49]  C. Krishna Mohan,et al.  Graph formulation of video activities for abnormal activity recognition , 2017, Pattern Recognit..

[50]  René Vidal,et al.  Sparse subspace clustering , 2009, CVPR.

[51]  Wei Zeng,et al.  Learning Deep Trajectory Descriptor for action recognition in videos using deep neural networks , 2015, 2015 IEEE International Conference on Multimedia and Expo (ICME).

[52]  Dino Pedreschi,et al.  Interactive visual clustering of large collections of trajectories , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[53]  Ioannis Katsavounidis,et al.  Low-Complexity Hand Gesture Recognition System for Continuous Streams of Digits and Letters , 2016, IEEE Transactions on Cybernetics.

[54]  Guangliang Chen,et al.  Spectral Curvature Clustering (SCC) , 2009, International Journal of Computer Vision.

[55]  Chiara Renso,et al.  Finding moving flock patterns among pedestrians through collective coherence , 2011, Int. J. Geogr. Inf. Sci..

[56]  Kamin Whitehouse,et al.  High-dimensional Time Series Clustering via Cross-Predictability , 2017, AISTATS.

[57]  Alfred O. Hero,et al.  Graph based k-means clustering , 2012, Signal Process..

[58]  Bingbing Ni,et al.  Motion Part Regularization: Improving action recognition via trajectory group selection , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[59]  Jae-Gil Lee,et al.  Traffic Density-Based Discovery of Hot Routes in Road Networks , 2007, SSTD.

[60]  Xing Xie,et al.  GeoLife: A Collaborative Social Networking Service among User, Location and Trajectory , 2010, IEEE Data Eng. Bull..

[61]  Nikos Pelekis,et al.  Algorithms for Nearest Neighbor Search on Moving Object Trajectories , 2007, GeoInformatica.

[62]  Trevor Darrell,et al.  Long-term recurrent convolutional networks for visual recognition and description , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[63]  Tianzhu Zhang,et al.  Learning semantic scene models by object classification and trajectory clustering , 2009, CVPR.

[64]  Krystian Mikolajczyk,et al.  Feature Tracking and Motion Compensation for Action Recognition , 2008, BMVC.

[65]  Jae-Gil Lee,et al.  Trajectory clustering: a partition-and-group framework , 2007, SIGMOD '07.

[66]  Mubarak Shah,et al.  Learning a Deep Model for Human Action Recognition from Novel Viewpoints , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[67]  Chong-Wah Ngo,et al.  Video event detection using motion relativity and visual relatedness , 2008, ACM Multimedia.

[68]  Petko Bakalov,et al.  On-line discovery of flock patterns in spatio-temporal data , 2009, GIS.

[69]  Göran Falkman,et al.  Online Learning and Sequential Anomaly Detection in Trajectories , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[70]  Yoichi Sato,et al.  Learning motion patterns and anomaly detection by Human trajectory analysis , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[71]  Jae-Gil Lee,et al.  Incremental Clustering for Trajectories , 2010, DASFAA.

[72]  Nicholas Roy,et al.  Topological mapping using spectral clustering and classification , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[73]  Pichao Wang,et al.  Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks , 2016, ACM Multimedia.

[74]  Cordelia Schmid,et al.  Learning realistic human actions from movies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[75]  Jianjiang Feng,et al.  Exploiting Unsupervised and Supervised Constraints for Subspace Clustering , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[76]  Youfu Li,et al.  On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition , 2016, IEEE Transactions on Cybernetics.

[77]  Kaiqi Huang,et al.  Gestalt laws based tracklets analysis for human crowd understanding , 2018, Pattern Recognit..

[78]  Martial Hebert,et al.  Representing Pairwise Spatial and Temporal Relations for Action Recognition , 2010, ECCV.

[79]  Chong-Wah Ngo,et al.  Trajectory-Based Modeling of Human Actions with Motion Reference Points , 2012, ECCV.

[80]  Sergio Escalera,et al.  A Gesture Recognition System for Detecting Behavioral Patterns of ADHD , 2014, IEEE Transactions on Cybernetics.

[81]  Abhinav Gupta,et al.  ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[82]  Kemal Leblebicioglu,et al.  Anomaly Detection and Activity Perception Using Covariance Descriptor for Trajectories , 2016, ECCV Workshops.

[83]  Xiaoqiang Lu,et al.  Statistical Hypothesis Detector for Abnormal Event Detection in Crowded Scenes , 2017, IEEE Transactions on Cybernetics.

[84]  Jun Li,et al.  ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[85]  Heng Tao Shen,et al.  Searching trajectories by locations: an efficiency study , 2010, SIGMOD Conference.

[86]  Xing Xie,et al.  Mining interesting locations and travel sequences from GPS trajectories , 2009, WWW '09.

[87]  Vania Bogorny,et al.  A clustering-based approach for discovering interesting places in trajectories , 2008, SAC '08.

[88]  Joachim Gudmundsson,et al.  Computing longest duration flocks in trajectory data , 2006, GIS '06.

[89]  Wei Jiang,et al.  Traffic Information Publication with Privacy Preservation , 2014, TIST.

[90]  Thomas Brinkhoff,et al.  A Framework for Generating Network-Based Moving Objects , 2002, GeoInformatica.

[91]  Cordelia Schmid,et al.  A Robust and Efficient Video Representation for Action Recognition , 2015, International Journal of Computer Vision.

[92]  Alberto Del Bimbo,et al.  Understanding Sport Activities from Correspondences of Clustered Trajectories , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[93]  Carol O'Sullivan,et al.  Globally Continuous and Non-Markovian Crowd Activity Analysis from Videos , 2016, ECCV.

[94]  Yannis Theodoridis,et al.  On the Generation of Spatiotemporal Datasets , 1999 .

[95]  Jing Yuan,et al.  On Discovery of Traveling Companions from Streaming Trajectories , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[96]  Cordelia Schmid,et al.  Activity representation with motion hierarchies , 2013, International Journal of Computer Vision.

[97]  Liang Lin,et al.  Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance , 2012, IEEE Transactions on Image Processing.

[98]  Vladlen Koltun,et al.  Dense scene reconstruction with points of interest , 2013, ACM Trans. Graph..

[99]  Dan Schonfeld,et al.  Real-Time Motion Trajectory-Based Indexing and Retrieval of Video Sequences , 2007, IEEE Transactions on Multimedia.

[100]  Nicholas Jing Yuan,et al.  On discovery of gathering patterns from trajectories , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[101]  Andrew Zisserman,et al.  Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.

[102]  Jean-Philippe Thiran,et al.  Counting Pedestrians in Video Sequences Using Trajectory Clustering , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[103]  Dilip B. Kotak,et al.  GRIDBSCAN: GRId Density-Based Spatial Clustering of Applications with Noise , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[104]  Shashi Shekhar,et al.  A partial join approach for mining co-location patterns , 2004, GIS '04.

[105]  Gerhard Rigoll,et al.  Novel Hybrid NN/HMM Modelling Techniques for On-line Handwriting Recognition , 2006 .

[106]  Francesco G. B. De Natale,et al.  Syntactic Matching of Trajectories for Ambient Intelligence Applications , 2009, IEEE Transactions on Multimedia.

[107]  Hongyuan Zha,et al.  Unsupervised Trajectory Clustering via Adaptive Multi-kernel-Based Shrinkage , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[108]  Alexandre Bernardino,et al.  Detection and classification of highway lanes using vehicle motion trajectories , 2006, IEEE Transactions on Intelligent Transportation Systems.

[109]  Philippe Salembier,et al.  Hierarchical Video Representation with Trajectory Binary Partition Tree , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[110]  Nikolaos Papanikolopoulos,et al.  Clustering of Vehicle Trajectories , 2010, IEEE Transactions on Intelligent Transportation Systems.

[111]  Bettina Speckmann,et al.  Efficient detection of motion patterns in spatio-temporal data sets , 2004, GIS '04.

[112]  Antonio Manuel López Peña,et al.  Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition , 2016, ECCV.

[113]  Yang Yi,et al.  Human action recognition with graph-based multiple-instance learning , 2016, Pattern Recognit..

[114]  Amit K. Roy-Chowdhury,et al.  A Continuous Learning Framework for Activity Recognition Using Deep Hybrid Feature Models , 2015, IEEE Transactions on Multimedia.

[115]  Tieniu Tan,et al.  A system for learning statistical motion patterns , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[116]  Jitendra Malik,et al.  Ieee Transactions on Pattern Analysis and Machine Intelligence Segmentation of Moving Objects by Long Term Video Analysis , 2022 .

[117]  Wei Chen,et al.  Action Detection by Implicit Intentional Motion Clustering , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[118]  Michel Bierlaire,et al.  Behavioral Priors for Detection and Tracking of Pedestrians in Video Sequences , 2006, International Journal of Computer Vision.

[119]  Chao Yuan,et al.  Deep Convolutional Factor Analyser for Multivariate Time Series Modeling , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

[120]  Thandar Thein,et al.  An Efficient Clustering Algorithm for Moving Object Trajectories , 2014 .

[121]  Wei Hu,et al.  A Coarse-to-Fine Strategy for Vehicle Motion Trajectory Clustering , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[122]  Zhongfei Zhang,et al.  An Incremental DPMM-Based Method for Trajectory Clustering, Modeling, and Retrieval , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[123]  Liang Lin,et al.  Trajectory parsing by cluster sampling in spatio-temporal graph , 2009, CVPR.

[124]  Iasonas Kokkinos,et al.  Discovering discriminative action parts from mid-level video representations , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[125]  Martial Hebert,et al.  Trajectons: Action recognition through the motion analysis of tracked features , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[126]  Alberto Del Bimbo,et al.  Submitted to Ieee Transactions on Cybernetics 1 3d Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold , 2022 .

[127]  Wei-Yang Lin,et al.  Trajectory-based sign language recognition using Discriminant Analysis in higher-dimensional feature space , 2011, 2011 IEEE International Conference on Multimedia and Expo.

[128]  Diansheng Guo,et al.  A graph-based approach to vehicle trajectory analysis , 2010, J. Locat. Based Serv..

[129]  Christoph Schnörr,et al.  Spectral clustering of linear subspaces for motion segmentation , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[130]  Osama Masoud,et al.  Learning Traffic Patterns at Intersections by Spectral Clustering of Motion Trajectories , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[131]  Willem H. Haemers,et al.  Spectra of Graphs , 2011 .

[132]  M. Trivedi,et al.  Learning trajectory patterns by clustering: Experimental studies and comparative evaluation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[133]  Jintao Li,et al.  Hierarchical spatio-temporal context modeling for action recognition , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[134]  Ming Dong,et al.  Detection of Abnormal Human Behavior Using a Matrix Approximation-Based Approach , 2014, 2014 13th International Conference on Machine Learning and Applications.

[135]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[136]  Jitendra Malik,et al.  Learning to segment moving objects in videos , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[137]  Robert B. Fisher,et al.  Semi-supervised Learning for Anomalous Trajectory Detection , 2008, BMVC.

[138]  Luc Van Gool,et al.  An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector , 2008, ECCV.

[139]  Dietmar Bauer,et al.  Track-Based Finding of Stopping Pedestrians - A Practical Approach for Analyzing a Public Infrastructure , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[140]  Alberto Del Bimbo,et al.  Motion segment decomposition of RGB-D sequences for human behavior understanding , 2017, Pattern Recognit..

[141]  Minsu Cho,et al.  Authority-shift clustering: Hierarchical clustering by authority seeking on graphs , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[142]  Francesco Solera,et al.  Socially Constrained Structural Learning for Groups Detection in Crowd , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[143]  Tieniu Tan,et al.  Comparison of Similarity Measures for Trajectory Clustering in Outdoor Surveillance Scenes , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[144]  Gian Luca Foresti,et al.  On-line trajectory clustering for anomalous events detection , 2006, Pattern Recognit. Lett..

[145]  Tieniu Tan,et al.  Trajectory Series Analysis based Event Rule Induction for Visual Surveillance , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[146]  Manuel Bouillon,et al.  Multi-criteria handwriting quality analysis with online fuzzy models , 2017, Pattern Recognit..

[147]  Dan Schonfeld,et al.  Object Trajectory-Based Activity Classification and Recognition Using Hidden Markov Models , 2007, IEEE Transactions on Image Processing.

[148]  Rama Chellappa,et al.  Entropy-Rate Clustering: Cluster Analysis via Maximizing a Submodular Function Subject to a Matroid Constraint , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[149]  Shuicheng Yan,et al.  Detecting Anomaly in Videos from Trajectory Similarity Analysis , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[150]  Tobias Schreck,et al.  Visual Cluster Analysis of Trajectory Data with Interactive Kohonen Maps , 2008, 2008 IEEE Symposium on Visual Analytics Science and Technology.

[151]  Silvio Savarese,et al.  Social LSTM: Human Trajectory Prediction in Crowded Spaces , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[152]  Simon J. Godsill,et al.  An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo , 2007, Proceedings of the IEEE.

[153]  Xi Chen,et al.  Classifying and visualizing motion capture sequences using deep neural networks , 2013, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

[154]  Dawei Liu,et al.  Efficient anomaly monitoring over moving object trajectory streams , 2009, KDD.

[155]  Mohan M. Trivedi,et al.  Surround vehicles trajectory analysis with recurrent neural networks , 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).

[156]  Gian Luca Foresti,et al.  Trajectory-Based Anomalous Event Detection , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[157]  Cordelia Schmid,et al.  Evaluation of Local Spatio-temporal Features for Action Recognition , 2009, BMVC.

[158]  Yi Yang,et al.  DevNet: A Deep Event Network for multimedia event detection and evidence recounting , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[159]  ZuWhan Kim.  Real time object tracking based on dynamic feature grouping with background subtraction , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[160]  Dino Pedreschi,et al.  Time-focused clustering of trajectories of moving objects , 2006, Journal of Intelligent Information Systems.

[161]  Jun Wang,et al.  Exploring Inter-feature and Inter-class Relationships with Deep Neural Networks for Video Classification , 2014, ACM Multimedia.

[162]  Cordelia Schmid,et al.  A Spatio-Temporal Descriptor Based on 3D-Gradients , 2008, BMVC.

[163]  Nikos Pelekis,et al.  Clustering Trajectories of Moving Objects in an Uncertain World , 2009, 2009 Ninth IEEE International Conference on Data Mining.

[164]  Yunjun Gao,et al.  Efficient k-Nearest-Neighbor Search Algorithms for Historical Moving Object Trajectories , 2007, Journal of Computer Science and Technology.

[165]  Xiaofang Zhou,et al.  Trajectory Indexing and Retrieval , 2011, Computing with Spatial Trajectories.

[166]  Shih-Fu Chang,et al.  Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.