17.1.2.1 Trajectory Analysis for Events, Actions

Hu, Z.H.[Zhao-Hua], Fan, X.[Xin], Song, Y.L.[Yao-Liang], Liang, D.Q.[De-Qun],
Joint trajectory tracking and recognition based on bi-directional nonlinear learning,
IVC(27), No. 9, 3 August 2009, pp. 1302-1312.
Elsevier DOI 0906
Visual tracking; Trajectory generative model; Autoencoder network; Nonlinear dimensionality reduction; Particle filter; Improved Hausdorff distance. Embeds high-dimensional trajectories into a two-dimensional plane. BibRef

Dyana, A., Das, S.[Sukhendu],
Trajectory representation using Gabor features for motion-based video retrieval,
PRL(30), No. 10, 15 July 2009, pp. 877-892.
Elsevier DOI 0906
Trajectory representation; Spectral features; Gabor filters; Partial trajectory matching; Edit distance; Motion-based video retrieval BibRef

Liu, H.W.[Hao-Wei], Sun, M.T.[Ming-Ting], Wu, R.C.[Ruei-Cheng], Yu, S.S.[Shiaw-Shian],
Automatic video activity detection using compressed domain motion trajectories for H.264 videos,
JVCIR(22), No. 5, July 2011, pp. 432-439.
Elsevier DOI 1106
Activity detection; Vehicle tracking; Compressed domain processing; H.264 videos; Object classification; Trajectory classification; Motion vector tracking; Residual error tracking BibRef

Karavasilis, V.[Vasileios], Nikou, C.[Christophoros], Likas, A.[Aristidis],
Visual tracking using the Earth Mover's Distance between Gaussian mixtures and Kalman filtering,
IVC(29), No. 5, April 2011, pp. 295-305.
Elsevier DOI 1103
Visual tracking; Gaussian mixture model (GMM); Expectation-Maximization (EM) algorithm; Differential Earth Mover's Distance (Differential EMD); Kalman filter BibRef

Karavasilis, V.[Vasileios], Blekas, K.[Konstantinos], Nikou, C.[Christophoros],
A novel framework for motion segmentation and tracking by clustering incomplete trajectories,
CVIU(116), No. 11, November 2012, pp. 1135-1148.
Elsevier DOI 1210
Motion segmentation; Visual feature tracking; Trajectory clustering; Sparse regression modeling
See also Matching mixtures of curves for human action recognition. BibRef

Karavasilis, V.[Vasileios], Nikou, C.[Christophoros], Likas, A.[Aristidis],
Visual tracking using spatially weighted likelihood of Gaussian mixtures,
CVIU(140), No. 1, 2015, pp. 43-57.
Elsevier DOI 1509
Visual tracking BibRef

Karavasilis, V.[Vasileios], Nikou, C.[Christophoros], Likas, A.[Aristidis],
Real time visual tracking using a spatially weighted von Mises mixture model,
PRL(90), No. 1, 2017, pp. 50-57.
Elsevier DOI 1704
Visual tracking BibRef

Hu, W.M.[Wei-Ming], Tian, G.D.[Guo-Dong], Li, X.[Xi], Maybank, S.J.[Stephen J.],
An Improved Hierarchical Dirichlet Process-Hidden Markov Model and Its Application to Trajectory Modeling and Retrieval,
IJCV(105), No. 3, December 2013, pp. 246-268.
Springer DOI 1309
BibRef

del-Bianco, C.R.[Carlos R.], Jaureguizar, F.[Fernando], Garcia, N.[Narciso],
Inference of Complex Trajectories by Means of a Multibehavior and Multiobject Tracking Algorithm,
CirSysVideo(23), No. 8, 2013, pp. 1300-1311.
IEEE DOI 1308
BibRef
Earlier:
Bayesian visual surveillance: A model for detecting and tracking a variable number of moving objects,
ICIP11(1437-1440).
IEEE DOI 1201
BibRef
Earlier:
Visual tracking of multiple interacting objects through Rao-Blackwellized Data Association Particle Filtering,
ICIP10(821-824).
IEEE DOI 1009
Calibration BibRef

Maqueda, A.I.[Ana I.], Ruano, A.[Arturo], del-Blanco, C.R.[Carlos R.], Carballeira, P.[Pablo], Jaureguizar, F.[Fernando], Garcia, N.[Narciso],
Novel multi-feature Bag-of-Words descriptor via subspace random projection for efficient human-action recognition,
AVSS15(1-6)
IEEE DOI 1511
Accuracy BibRef

Lin, W.Y.[Wei-Yang], Hsieh, C.Y.[Chung-Yang],
Kernel-based representation for 2D/3D motion trajectory retrieval and classification,
PR(46), No. 3, March 2013, pp. 662-670.
Elsevier DOI 1212
Discriminant analysis; Kernel method; Trajectory representation; Trajectory-based retrieval; Trajectory-based classification BibRef

Celeux, G.[Gilles], Nascimento, J.C.[Jacinto C.], Marques, J.S.[Jorge S.],
Learning switching dynamic models for objects tracking,
PR(37), No. 9, September 2004, pp. 1841-1853.
Elsevier DOI 0407
BibRef

Nascimento, J.C.[Jacinto C.], Figueiredo, M.A.T.[Mário A.T.], Marques, J.S.[Jorge S.],
Trajectory Classification Using Switched Dynamical Hidden Markov Models,
IP(19), No. 5, May 2010, pp. 1338-1348.
IEEE DOI 1004

See also Similarity-Based Classification of Sequences Using Hidden Markov Models. BibRef

Nascimento, J.C.[Jacinto C.], Figueiredo, M.A.T.[Mário A.T.], Marques, J.S.[Jorge S.],
Activity Recognition Using a Mixture of Vector Fields,
IP(22), No. 5, May 2013, pp. 1712-1725.
IEEE DOI 1303
BibRef
Earlier:
Trajectory analysis in natural images using mixtures of vector fields,
ICIP09(4353-4356).
IEEE DOI 0911
BibRef
And:
Trajectory Modeling Using Mixtures of Vector Fields,
IbPRIA09(40-47).
Springer DOI 0906
BibRef

Portêlo, A.[Ana], Cavallaro, A.[Andrea], Barata, C.[Catarina], Marques, J.S.[Jorge S.],
Description and Recognition of Activity Patterns Using Sparse Vector Fields,
IbPRIA19(I:239-248).
Springer DOI 1910
BibRef

Marques, J.S.[Jorge S.], Barão, M.[Miguel], Lemos, J.M.[João M.],
Alignment of velocity fields for video surveillance,
PRL(33), No. 12, 1 September 2012, pp. 1632-1637.
Elsevier DOI 1208
Image analysis; Image alignment; Motion analysis; Video surveillance BibRef

Nascimento, J.C.[Jacinto C.], Marques, J.S.[Jorge S.],
Improving the robustness of gradient vector flow in cluttered images,
ICIP10(657-660).
IEEE DOI 1009

See also Improving the robustness of parametric shape tracking with switched multiple models. BibRef

Barata, C., Lemos, J.M.[Joao M.], Marques, J.S.[Jorge S.],
Estimation of Space-Varying Covariance Matrices,
ICIP18(4003-4007)
IEEE DOI 1809
Trajectory, Covariance matrices, Switches, Estimation, Uncertainty, Interpolation, Dictionaries, Human motion, space-varying covariance matrices BibRef

Marques, J.S.[Jorge S.], Lemos, J.M.[João M.], Figueiredo, M.A.T.[Mário A.T.], Nascimento, J.C.[Jacinto C.], Barão, M.[Miguel],
Trajectory Analysis Using Switched Motion Fields: A Parametric Approach,
IbPRIA11(420-427).
Springer DOI 1106
BibRef

Nascimento, J.C.[Jacinto C.], Marques, J.S.[Jorge S.], Lemos, J.M.[Joao M.],
Modeling and Classifying Human Activities From Trajectories Using a Class of Space-Varying Parametric Motion Fields,
IP(22), No. 5, May 2013, pp. 2066-2080.
IEEE DOI 1304
BibRef
Earlier:
A class of space-varying parametric motion fields for human activity recognition,
ICIP12(761-764).
IEEE DOI 1302
BibRef
Earlier:
Flexible trajectory modeling using a mixture of parametric motion fields for video surveillance,
ICIP11(1413-1416).
IEEE DOI 1201
BibRef

Cancela, B.[Brais], Ortega, M.[Marcos], Penedo, M.G.[Manuel G.], Novo, J., Barreira, N.,
On the use of a minimal path approach for target trajectory analysis,
PR(46), No. 7, July 2013, pp. 2015-2027.
Elsevier DOI 1303
Online trajectory analysis; Dynamic potential; Abnormal behavior detection; Minimal path; Geodesic active contours BibRef

Cancela, B.[Brais], Ortega, M.[Marcos], Penedo, M.G.[Manuel G.],
Path Analysis Using Directional Forces. A Practical Case: Traffic Scenes,
IbPRIA13(366-373).
Springer DOI 1307
BibRef

Cancela, B.[Brais], Ortega, M.[Marcos], Fernández, A.[Alba],
Trajectory Similarity Measures Using Minimal Paths,
CIAP13(I:400-409).
Springer DOI 1311
BibRef

Cancela, B.[Brais], Ortega, M.[Marcos], Fernández, A.[Alba], Penedo, M.G.[Manuel G.],
Path Analysis in Multiple-Target Video Sequences,
CIAP11(II: 50-59).
Springer DOI 1109
BibRef
Earlier: A1, A2, A4, A3:
Solving Multiple-Target Tracking Using Adaptive Filters,
ICIAR11(I: 416-425).
Springer DOI 1106
BibRef

Lin, L.[Liang], Lu, Y.Y.[Yong-Yi], Pan, Y.[Yan], Chen, X.W.[Xiao-Wu],
Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance,
IP(21), No. 12, December 2012, pp. 4844-4857.
IEEE DOI 1212
BibRef

Wang, H.[Heng], Kläser, A.[Alexander], Schmid, C.[Cordelia], Liu, C.L.[Cheng-Lin],
Dense Trajectories and Motion Boundary Descriptors for Action Recognition,
IJCV(103), No. 1, May 2013, pp. 60-79.
Springer DOI 1305
BibRef
Earlier:
Action recognition by dense trajectories,
CVPR11(3169-3176).
IEEE DOI 1106
BibRef

Wang, H.[Heng], Schmid, C.[Cordelia],
Action Recognition with Improved Trajectories,
ICCV13(3551-3558)
IEEE DOI 1403
BibRef

Hu, W.M.[Wei-Ming], Li, X.[Xi], Tian, G.D.[Guo-Dong], Maybank, S.J.[Stephen J.], Zhang, Z.F.[Zhong-Fei],
An Incremental DPMM-Based Method for Trajectory Clustering, Modeling, and Retrieval,
PAMI(35), No. 5, May 2013, pp. 1051-1065.
IEEE DOI 1304
Dirichlet process mixture model, Trajectory clustering and modeling, incremental clustering, time-sensitive Dirichlet process mixture model, video retrieval BibRef

Parent, C.[Christine], Spaccapietra, S.[Stefano], Renso, C.[Chiara], Andrienko, G.[Gennady], Andrienko, N.[Natalia], Bogorny, V.[Vania], Damiani, M.L.[Maria Luisa], Gkoulalas-Divanis, A.[Aris], Macedo, J.[Jose], Pelekis, N.[Nikos], Theodoridis, Y.[Yannis], Yan, Z.X.[Zhi-Xian],
Semantic trajectories modeling and analysis,
Surveys(45), No. 2, February 2013, pp. Article No 42.
DOI Link 1309
Survey, Trajectory Analysis. Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented BibRef

Anagnostopoulos, C., Hadjiefthymiades, S.,
Intelligent Trajectory Classification for Improved Movement Prediction,
SMCS(44), No. 10, October 2014, pp. 1301-1314.
IEEE DOI 1410
knowledge based systems BibRef

Chen, X.G.[Xiao-Gang], Ye, Q.X.[Qi-Xiang], Zou, J.L.[Jia-Ling], Li, C.[Ce], Cui, Y.T.[Yan-Ting], Jiao, J.B.[Jian-Bin],
Visual trajectory analysis via Replicated Softmax-based models,
SIViP(8), No. S1, December 2014, pp. 183-190.
Springer DOI 1411
BibRef

Zhang, S.[Shun], Wang, J.J.[Jin-Jun], Wang, Z.[Zelun], Gong, Y.H.[Yi-Hong], Liu, Y.H.[Yue-Hu],
Multi-target tracking by learning local-to-global trajectory models,
PR(48), No. 2, 2015, pp. 580-590.
Elsevier DOI 1411
Local-to-global BibRef

Wang, Z.[Zelun], Wang, J.J.[Jin-Jun], Zhang, S.[Shun], Gong, Y.H.[Yi-Hong],
Visual tracking based on online sparse feature learning,
IVC(38), No. 1, 2015, pp. 24-32.
Elsevier DOI 1506
Visual tracking BibRef

Wang, T., Zhang, D., Zhou, X., Qi, X., Ni, H., Wang, H., Zhou, G.,
Mining Personal Frequent Routes via Road Corner Detection,
SMCS(46), No. 4, April 2016, pp. 445-458.
IEEE DOI 1604
Clustering algorithms BibRef

Xiang, L.G.[Long-Gang], Gao, M.[Meng], Wu, T.[Tao],
Extracting Stops from Noisy Trajectories: A Sequence Oriented Clustering Approach,
IJGI(5), No. 3, 2016, pp. 29.
DOI Link 1604
BibRef

Lai, T.T.[Tao-Tao], Wang, H.Z.[Han-Zi], Yan, Y.[Yan], Chin, T.J.[Tat-Jun], Zhao, W.L.[Wan-Lei],
Motion Segmentation Via a Sparsity Constraint,
ITS(18), No. 4, April 2017, pp. 973-983.
IEEE DOI 1704
Computational modeling. Trajectory segmentation. BibRef

Luo, T.[Ting], Zheng, X.W.[Xin-Wei], Xu, G.[Guangluan], Fu, K.[Kun], Ren, W.J.[Wen-Juan],
An Improved DBSCAN Algorithm to Detect Stops in Individual Trajectories,
IJGI(6), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Lin, W.Y.[Wei-Yao], Zhou, Y.[Yang], Xu, H.T.[Hong-Teng], Yan, J.C.[Jun-Chi], Xu, M.L.[Ming-Liang], Wu, J.X.[Jian-Xin], Liu, Z.C.[Zi-Cheng],
A Tube-and-Droplet-Based Approach for Representing and Analyzing Motion Trajectories,
PAMI(39), No. 8, August 2017, pp. 1489-1503.
IEEE DOI 1707
Representing motion trajectories. Context modeling, Electron tubes, Hidden Markov models, Shape, Trajectory, 3D action recognition, 3D tube, Trajectory representation, abnormality detection, trajectory analysis. BibRef

Guo, S.[Sheng], Xiong, H.J.[Han-Jiang], Zheng, X.W.[Xian-Wei],
A Novel Semantic Matching Method for Indoor Trajectory Tracking,
IJGI(6), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Qian, H.Z.[Hai-Zhong], Lu, Y.M.[Yong-Mei],
Simplifying GPS Trajectory Data with Enhanced Spatial-Temporal Constraints,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Guo, N.[Ning], Ma, M.Y.[Meng-Yu], Xiong, W.[Wei], Chen, L.[Luo], Jing, N.[Ning],
An Efficient Query Algorithm for Trajectory Similarity Based on Fréchet Distance Threshold,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Jia, T.[Tao], Ji, Z.[Zheng],
Understanding the Functionality of Human Activity Hotspots from Their Scaling Pattern Using Trajectory Data,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Timofte, R.[Radu], Kwon, J.[Junseok], Van Gool, L.J.[Luc J.],
PICASO: PIxel correspondences and SOft match selection for real-time tracking,
CVIU(153), No. 1, 2016, pp. 151-162.
Elsevier DOI 1612
Visual tracking BibRef

Kwon, J.[Junseok], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Leveraging observation uncertainty for robust visual tracking,
CVIU(158), No. 1, 2017, pp. 62-71.
Elsevier DOI 1704
Object tracking BibRef

Manen, S.[Santiago], Timofte, R., Dai, D., Van Gool, L.J.[Luc J.],
Leveraging single for multi-target tracking using a novel trajectory overlap affinity measure,
WACV16(1-9)
IEEE DOI 1606
Atmospheric measurements BibRef

Manen, S.[Santiago], Gygli, M., Dai, D., Van Gool, L.J.[Luc J.],
PathTrack: Fast Trajectory Annotation with Path Supervision,
ICCV17(290-299)
IEEE DOI 1802
image motion analysis, image sequences, learning (artificial intelligence), object recognition, Trajectory BibRef

Li, J.P.[Jia-Peng], Chen, W.[Wei], Liu, A.[An], Li, Z.X.[Zhi-Xu], Zhao, L.[Lei],
FTS: a feature-preserving trajectory synthesis model,
GeoInfo(22), No. 1, January 2018, pp. 49-70.
Springer DOI 1802
Trajectory datasets from GPS data. BibRef

Zou, Y.B.[Ye-Bin], Chen, Y.J.[Yi-Jin], He, J.[Jing], Pang, G.[Gehu], Zhang, K.X.[Kai-Xuan],
4D Time Density of Trajectories: Discovering Spatiotemporal Patterns in Movement Data,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Zhao, H.D.[Han-Dong], Ding, Z.M.[Zheng-Ming], Fu, Y.[Yun],
Ensemble Subspace Segmentation Under Blockwise Constraints,
CirSysVideo(28), No. 7, July 2018, pp. 1526-1539.
IEEE DOI 1807
Tracks of moving objects. Computational efficiency, Face, Image segmentation, Motion segmentation, Optimization, Robustness, Sparse matrices, sparse graph BibRef

Li, J.[Jing], Wang, X.T.[Xuan-Tong], Zhang, T.[Tong], Xu, Y.[You],
Efficient Parallel K Best Connected Trajectory (K-BCT) Query with GPGPU: A Combinatorial Min-Distance and Progressive Bounding Box Approach,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link 1808
Similarity of trajectories. BibRef

Xu, J.Q.[Jian-Qiu], Güting, R.H.[Ralf Hartmut], Gao, Y.J.[Yun-Jun],
Continuous k nearest neighbor queries over large multi-attribute trajectories: a systematic approach,
GeoInfo(22), No. 4, October 2018, pp. 723-766.
WWW Link. 1811
BibRef

Zhang, Y.[Yue], Lin, Y.P.[Ya-Ping],
An interactive method for identifying the stay points of the trajectory of moving objects,
JVCIR(59), 2019, pp. 387-392.
Elsevier DOI 1903
Trajectory, Stay point, Space-time cube BibRef

Saini, R.[Rajkumar], Roy, P.P.[Partha Pratim], Dogra, D.P.[Debi Prosad],
A novel point-line duality feature for trajectory classification,
VC(35), No. 3, March 2019, pp. 415-427.
Springer DOI 1906
BibRef

Chen, R.[Rui], Chen, M.J.[Ming-Jian], Li, W.L.[Wan-Li], Wang, J.G.[Jian-Guang], Yao, X.[Xiang],
Mobility Modes Awareness from Trajectories Based on Clustering and a Convolutional Neural Network,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Pulshashi, I.R.[Iq Reviessay], Bae, H.[Hyerim], Choi, H.[Hyunsuk], Mun, S.[Seunghwan], Sutrisnowati, R.A.[Riska Asriana],
Simplification and Detection of Outlying Trajectories from Batch and Streaming Data Recorded in Harsh Environments,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Cutrona, V.[Vincenzo], Bianchi, F.[Federico], Ciavotta, M.[Michele], Maurino, A.[Andrea],
On the composition and recommendation of multi-feature paths: a comprehensive approach,
GeoInfo(23), No. 3, July 2019, pp. 353-373.
Springer DOI 1908
From GPS trackers. BibRef

Shirazi, M.S.[Mohammad Shokrolah], Morris, B.T.[Brendan Tran],
Trajectory prediction of vehicles turning at intersections using deep neural networks,
MVA(30), No. 6, September 2019, pp. 1097-1109.
WWW Link. 1909
BibRef

Gatziolis, D.[Demetrios], McGaughey, R.J.[Robert J.],
Reconstructing Aircraft Trajectories from Multi-Return Airborne Laser-Scanning Data,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Yang, T.[Tao], Li, D.D.[Dong-Dong], Bai, Y.[Yi], Zhang, F.B.[Fang-Bing], Li, S.[Sen], Wang, M.[Miao], Zhang, Z.Y.[Zhuo-Yue], Li, J.[Jing],
Multiple-Object-Tracking Algorithm Based on Dense Trajectory Voting in Aerial Videos,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Su, B.[Bing], Hua, G.[Gang],
Order-Preserving Optimal Transport for Distances between Sequences,
PAMI(41), No. 12, December 2019, pp. 2961-2974.
IEEE DOI 1911
Distance between sequences. Solid modeling, Distortion, Legged locomotion, Distortion measurement, Supervised learning, Optimal transport, inverse difference moment BibRef

Guo, N.[Ning], Shekhar, S.[Shashi], Xiong, W.[Wei], Chen, L.[Luo], Jing, N.[Ning],
UTSM: A Trajectory Similarity Measure Considering Uncertainty Based on an Amended Ellipse Model,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Ribeiro de Almeida, D.[Damião], de Souza Baptista, C.[Cláudio], Gomes de Andrade, F.[Fabio], Soares, A.[Amilcar],
A Survey on Big Data for Trajectory Analytics,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Salas, J.[Julián], Megías, D.[David], Torra, V.[Vicenç], Toger, M.[Marina], Dahne, J.[Joel], Sainudiin, R.[Raazesh],
Swapping trajectories with a sufficient sanitizer,
PRL(131), 2020, pp. 474-480.
Elsevier DOI 2004
Privacy preserving mobility data mining, Real-time mobility data anonymization, Origin-Destination matrices BibRef

Chen, C., Ding, Y., Xie, X., Zhang, S., Wang, Z., Feng, L.,
TrajCompressor: An Online Map-matching-based Trajectory Compression Framework Leveraging Vehicle Heading Direction and Change,
ITS(21), No. 5, May 2020, pp. 2012-2028.
IEEE DOI 2005
Trajectory, Global Positioning System, Roads, Presses, Data centers, Urban areas, Task analysis, Vehicle trajectory compression, mobile environment BibRef

Faisal, M., Akhter, I., Ali, M., Hartley, R.I.,
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency,
WACV20(1873-1882)
IEEE DOI 2006
Trajectory, Optical imaging, Motion segmentation, Robustness, Tensile stress, Optical fiber networks BibRef

Campo, D., Baydoun, M., Marin, P., Martin, D., Marcenaro, L., de la Escalera, A., Regazzoni, C.S.,
Learning Probabilistic Awareness Models for Detecting Abnormalities in Vehicle Motions,
ITS(21), No. 3, March 2020, pp. 1308-1320.
IEEE DOI 2003
Trajectory, Vehicle dynamics, Hidden Markov models, Dynamics, Data models, Intelligent systems, Smart mobility, decision systems BibRef

Campo, D., Baydoun, M., Marcenaro, L., Cavallaro, A., Regazzoni, C.S.,
Unsupervised Trajectory Modeling Based on Discrete Descriptors for Classifying Moving Objects in Video Sequences,
ICIP18(833-837)
IEEE DOI 1809
BibRef
Earlier:
Modeling and classification of trajectories based on a Gaussian process decomposition into discrete components,
AVSS17(1-6)
IEEE DOI 1806
BibRef
Earlier: A1, A2, A3, A5, Only:
Task-dependent saliency estimation from trajectories of agents in video sequences,
ICIP17(4252-4256)
IEEE DOI 1803
Trajectory, Vocabulary, Neurons, Video sequences, Self-organizing feature maps, Data models, Training, trajectory classification. Gaussian processes, data handling, image classification, image motion analysis, image segmentation, regression analysis, Uncertainty. Heuristic algorithms, Image color analysis, Task analysis, Transforms, Visualization, vector field representation BibRef

Moreira, T.P.[Thierry Pinheiro], Menotti, D.[David], Pedrini, H.[Helio],
Video action recognition based on visual rhythm representation,
JVCIR(71), 2020, pp. 102771.
Elsevier DOI 2009
a methodology of volume description (spact-time volume). Action recognition, Visual rhythm, Video sequences, Computer vision BibRef

Niu, X., Chen, T., Wu, C.Q., Niu, J., Li, Y.,
Label-Based Trajectory Clustering in Complex Road Networks,
ITS(21), No. 10, October 2020, pp. 4098-4110.
IEEE DOI 2010
Trajectory, Roads, Clustering algorithms, Complex networks, Euclidean distance, Computational modeling, Bayes methods, dual graph BibRef

Huang, Z.[Zhi], Wang, J.[Jun], Pi, L.[Lei], Song, X.L.[Xiao-Lin], Yang, L.F.[Ling-Fang],
LSTM based trajectory prediction model for cyclist utilizing multiple interactions with environment,
PR(112), 2021, pp. 107800.
Elsevier DOI 2102
Trajectory prediction, Interaction, Cyclist, LSTM, Focal attention mechanism BibRef

Li, S.Y.[Song-Yuan], Tian, H.[Hui], Shen, H.[Hong], Sang, Y.P.[Ying-Peng],
Privacy-Preserving Trajectory Data Publishing by Dynamic Anonymization with Bounded Distortion,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Zhu, J.[Jin], Cheng, D.[Dayu], Zhang, W.W.[Wei-Wei], Song, C.[Ci], Chen, J.[Jie], Pei, T.[Tao],
A New Approach to Measuring the Similarity of Indoor Semantic Trajectories,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Wang, S.[Sheng], Bao, Z.F.[Zhi-Feng], Culpepper, J.S.[J. Shane], Cong, G.[Gao],
A Survey on Trajectory Data Management, Analytics, and Learning,
Surveys(54), No. 2, March 2021, pp. xx-yy.
DOI Link 2104
Survey, Trajectory Analysis. similarity search, storage system, deep learning, urban analytics, Trajectory BibRef

Zhang, K.X.[Kai-Xuan], Zhao, D.B.[Dong-Bao], Feng, L.L.[Lin-Lin], Cao, L.H.[Lian-Hai],
Cycling Trajectory-Based Navigation Independent of Road Network Data Support,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Bertugli, A.[Alessia], Calderara, S.[Simone], Coscia, P.[Pasquale], Ballan, L.[Lamberto], Cucchiara, R.[Rita],
AC-VRNN: Attentive Conditional-VRNN for multi-future trajectory prediction,
CVIU(210), 2021, pp. 103245.
Elsevier DOI 2109
Trajectory forecasting, Multi-future prediction, Time series, Variational recurrent neural networks, Graph attention networks BibRef

Monti, A.[Alessio], Bertugli, A.[Alessia], Calderara, S.[Simone], Cucchiara, R.[Rita],
DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting,
ICPR21(2551-2558)
IEEE DOI 2105
Urban areas, Predictive models, Graph neural networks, Trajectory, Pattern recognition, Proposals, Forecasting BibRef

Landi, F.[Federico], Baraldi, L.[Lorenzo], Cornia, M.[Marcella], Corsini, M.[Massimiliano], Cucchiara, R.[Rita],
Multimodal attention networks for low-level vision-and-language navigation,
CVIU(210), 2021, pp. 103255.
Elsevier DOI 2109
Vision-and-language navigation, Embodied AI, Multi-modal attention BibRef

Bigazzi, R.[Roberto], Landi, F.[Federico], Cornia, M.[Marcella], Cascianelli, S.[Silvia], Baraldi, L.[Lorenzo], Cucchiara, R.[Rita],
Explore and Explain: Self-supervised Navigation and Recounting,
ICPR21(1152-1159)
IEEE DOI 2105
Measurement, Navigation, Natural languages, Trajectory, Pattern recognition, Intelligent agents, Artificial intelligence BibRef

Saini, R.[Rajkumar], Kumar, P.[Pradeep], Roy, P.P.[Partha Pratim], Pal, U.[Umapada],
Modeling local and global behavior for trajectory classification using graph based algorithm,
PRL(150), 2021, pp. 280-288.
Elsevier DOI 2109
Trajectory classification and clustering, Dynamic time warping (DTW), Minimum spanning tree (MST) BibRef

Vidal-Filho, J.N.[Jarbas Nunes], Times, V.C.[Valéria Cesário], Lisboa-Filho, J.[Jugurta], Renso, C.[Chiara],
Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures,
IJGI(10), No. 12, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Wang, Y.[Yu], Zhao, S.J.[Sheng-Jie], Zhang, R.Q.[Rong-Qing], Cheng, X.[Xiang], Yang, L.Q.[Liu-Qing],
Multi-Vehicle Collaborative Learning for Trajectory Prediction With Spatio-Temporal Tensor Fusion,
ITS(23), No. 1, January 2022, pp. 236-248.
IEEE DOI 2201
Predict other vehicle trajectories. Trajectory, Predictive models, Generative adversarial networks, Collaborative work, Tensile stress, Intelligent vehicles, generative adversarial networks BibRef

Wang, Y.[Yu], Chen, S.W.[Shi-Wei],
Multi-Agent Trajectory Prediction With Spatio-Temporal Sequence Fusion,
MultMed(25), 2023, pp. 13-23.
IEEE DOI 2301
Analytical models, Correlation, Graphical models, Buildings, Trajectory, Intelligent transportation systems, sequence-to-sequence BibRef

Jimoh, B.[Biliaminu], Mariescu-Istodor, R.[Radu], Fränti, P.[Pasi],
Is Medoid Suitable for Averaging GPS Trajectories?,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Xia, B.H.[Bei-Hao], Wong, C.H.[Cong-Hao], Peng, Q.[Qinmu], Yuan, W.[Wei], You, X.G.[Xin-Ge],
CSCNet: Contextual semantic consistency network for trajectory prediction in crowded spaces,
PR(126), 2022, pp. 108552.
Elsevier DOI 2204
Trajectory prediction, The context-aware transfer, The conditional context loss BibRef

Maczyta, L.[Léo], Bouthemy, P.[Patrick], Le Meur, O.[Olivier],
Trajectory Saliency Detection Using Consistency-Oriented Latent Codes From a Recurrent Auto-Encoder,
CirSysVideo(32), No. 4, April 2022, pp. 1724-1738.
IEEE DOI 2204
Trajectory, Videos, Image reconstruction, Saliency detection, Dynamics, Training, Generative adversarial networks, recurrent auto-encoder BibRef

Qiao, D.[Dianfeng], Yang, X.Y.[Xin-Yu], Liang, Y.[Yan], Hao, X.H.[Xiao-Hui],
Rapid trajectory clustering based on neighbor spatial analysis,
PRL(156), 2022, pp. 167-173.
Elsevier DOI 2205
Trajectory clustering, Trajectory-Hausdorff distance, Shared nearest neighbor, Similarity matrix, R-tree BibRef

Horak, J.[Jiri], Kukuliac, P.[Pavel], Maresova, P.[Petra], Orlikova, L.[Lucie], Kolodziej, O.[Ondrej],
Spatial Pattern of the Walkability Index, Walk Score and Walk Score Modification for Elderly,
IJGI(11), No. 5, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Qian, S.Y.[Shi-You], Cheng, B.[Bin], Cao, J.[Jian], Xue, G.T.[Guang-Tao], Zhu, Y.M.[Yan-Min], Yu, J.[Jiadi], Li, M.L.[Ming-Lu], Zhang, T.[Tao],
Detecting Taxi Trajectory Anomaly Based on Spatio-Temporal Relations,
ITS(23), No. 7, July 2022, pp. 6883-6894.
IEEE DOI 2207
Trajectory, Public transportation, Transportation, Testing, Feature extraction, Roads, Computer science, Anomaly detection, spatio-temporal BibRef

Neves, F.[Francisco], Finamore, A.C.[Anna C.], Madeira, S.C.[Sara C.], Henriques, R.[Rui],
Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering,
ITS(23), No. 7, July 2022, pp. 6430-6445.
IEEE DOI 2207
Roads, Urban areas, Geology, Trajectory, Time series analysis, Spatiotemporal phenomena, Detectors, Sustainable mobility, road traffic data BibRef

Cao, Q.[Qi], Ren, G.[Gang], Li, D.W.[Da-Wei], Li, H.J.[Hao-Jie], Ma, J.[Jiangshan],
Map Matching for Sparse Automatic Vehicle Identification Data,
ITS(23), No. 7, July 2022, pp. 6495-6508.
IEEE DOI 2207
Global Positioning System, Hidden Markov models, Trajectory, Vehicles, Roads, Tracking, Radiofrequency identification, AVI data, sparsity issue BibRef

Xiao, J.H.[Jian-Hua], Xiao, Z.[Zhu], Wang, D.[Dong], Havyarimana, V.[Vincent], Liu, C.X.[Chen-Xi], Zou, C.M.[Cheng-Ming], Wu, D.[Di],
Vehicle Trajectory Interpolation Based on Ensemble Transfer Regression,
ITS(23), No. 7, July 2022, pp. 7680-7691.
IEEE DOI 2207
Trajectory, Interpolation, Global navigation satellite system, Training, Roads, Urban areas, Data models, ensemble learning BibRef

Liu, Y.[Yang], Wu, F.[Fanyou], Lyu, C.[Cheng], Liu, X.[Xin], Liu, Z.Y.[Zhi-Yuan],
Behavior2vector: Embedding Users' Personalized Travel Behavior to Vector,
ITS(23), No. 7, July 2022, pp. 8346-8355.
IEEE DOI 2207
Navigation, Unsupervised learning, Principal component analysis, Web and internet services, Trajectory, Numerical models, embedding vector BibRef

Belhadi, A.[Asma], Djenouri, Y.[Youcef], Djenouri, D.[Djamel], Michalak, T.[Tomasz], Lin, J.C.W.[Jerry Chun-Wei],
Deep Learning Versus Traditional Solutions for Group Trajectory Outliers,
Cyber(52), No. 6, June 2022, pp. 4508-4519.
IEEE DOI 2207
Trajectory, Anomaly detection, Feature extraction, Correlation, Deep learning, Computational modeling, Hurricanes, trajectory data BibRef

Zhang, K.X.[Kai-Xuan], Zhao, D.[Dongbao], Liu, W.K.[Wen-Kai],
Online vehicle trajectory compression algorithm based on motion pattern recognition,
IET-ITS(16), No. 8, 2022, pp. 998-1010.
DOI Link 2207
BibRef

Ribeiro de Almeida, D.[Damião], de Souza Baptista, C.[Cláudio], de Andrade, F.G.[Fabio Gomes],
Similarity Search on Semantic Trajectories Using Text Processing,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Ahmed, U.[Usman], Srivastava, G.[Gautam], Djenouri, Y.[Youcef], Lin, J.C.W.[Jerry Chun-Wei],
Deviation Point Curriculum Learning for Trajectory Outlier Detection in Cooperative Intelligent Transport Systems,
ITS(23), No. 9, September 2022, pp. 16514-16523.
IEEE DOI 2209
Trajectory, Public transportation, Anomaly detection, Roads, Monitoring, Intelligent sensors, Databases, Trajectory analysis, smart city application BibRef

Hu, W.[Wenya], Li, W.M.[Wei-Min], Zhou, X.K.[Xiao-Kang], Kawai, A.[Akira], Fueda, K.[Kaoru], Qian, Q.[Quan], Wang, J.J.[Jian-Jia],
Spatio-Temporal Graph Convolutional Networks via View Fusion for Trajectory Data Analytics,
ITS(24), No. 4, April 2023, pp. 4608-4620.
IEEE DOI 2304
Trajectory, Convolution, Feature extraction, Sensors, Predictive models, Task analysis, Data mining, traffic forecasting BibRef

Schaffert, M.[Markus], Geist, K.[Konstantin], Albrecht, J.[Jonathan], Enners, D.[Dorothea], Müller, H.[Hartmut],
Walk Score from 2D to 3D: Walkability for the Elderly in Two Medium-Sized Cities in Germany,
IJGI(12), No. 4, 2023, pp. 157.
DOI Link 2305
BibRef

Marchetti, F.[Francesco], Becattini, F.[Federico], Seidenari, L.[Lorenzo], del Bimbo, A.[Alberto],
Multiple Trajectory Prediction of Moving Agents With Memory Augmented Networks,
PAMI(45), No. 6, June 2023, pp. 6688-6702.
IEEE DOI 2305
BibRef
Earlier:
MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction,
CVPR20(7141-7150)
IEEE DOI 2008
Trajectory, Navigation, Predictive models, Autonomous vehicles, Safety, Sensors, Robots, Trajectory prediction, autonomous driving. Encoding, Task analysis, Decoding, Recurrent neural networks BibRef

Kang, Y.[Youngok], Kim, J.[Jiyeon], Park, J.Y.[Ji-Young], Lee, J.[Jiyoon],
Assessment of Perceived and Physical Walkability Using Street View Images and Deep Learning Technology,
IJGI(12), No. 5, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Zhang, Y.Z.[Yu-Zhen], Guo, W.Z.[Wei-Zhi], Su, J.[Junning], Lv, P.[Pei], Xu, M.L.[Ming-Liang],
BIP-Tree: Tree Variant With Behavioral Intention Perception for Heterogeneous Trajectory Prediction,
ITS(24), No. 9, September 2023, pp. 9584-9598.
IEEE DOI 2310
BibRef

Han, S.J.[Shi-Jing], Wang, H.D.[Hua-Dong], Hao, X.Y.[Xiang-Yang], Miao, S.F.[Shu-Feng],
3D Geographic Trajectories' Generation and Visualization of Dynamic Objects in Surveillance Videos,
ICIVC22(669-673)
IEEE DOI 2301
Solid modeling, Visualization, Target tracking, Surveillance, Dynamics, Redundancy, surveillance video, mapping model, object tracking BibRef

Persson, M.[Mikael], Häger, G.[Gustav], Ovrén, H.[Hannes], Forssén, P.E.[Per-Erik],
Practical Pose Trajectory Splines With Explicit Regularization,
3DV21(156-165)
IEEE DOI 2201
Extrapolation, Estimation, Real-time systems, Trajectory, Calibration, Splines (mathematics), Pose Trajectory, spline BibRef

Rossi, S.[Silvia], Viola, I.[Irene], Toni, L.[Laura], Cesar, P.[Pablo],
A New Challenge: Behavioural Analysis of 6-DOF User When Consuming Immersive Media,
ICIP21(3423-3427)
IEEE DOI 2201
Measurement, Solid modeling, Navigation, Heuristic algorithms, Wearable computers, Simulation, Virtual reality, Point Cloud, Data Clustering BibRef

Huang, R.[Renhao], Song, Y.[Yang], Pagnucco, M.[Maurice],
An Improved Discriminator for GAN-Based Trajectory Prediction Models,
DICTA20(1-3)
IEEE DOI 2201
Training, Recurrent neural networks, Computational modeling, Stochastic processes, Predictive models, Trajectory, Robots BibRef

Alfani, A.[Alessandra], Becattini, F.[Federico], Seidenari, L.[Lorenzo], del Bimbo, A.[Alberto],
Online Deep Clustering with Video Track Consistency,
ICPR22(2650-2656)
IEEE DOI 2212
Visualization, Annotations, Cameras, Generators, Noise measurement, Task analysis BibRef

Berlincioni, L.[Lorenzo], Becattini, F.[Federico], Seidenari, L.[Lorenzo], del Bimbo, A.[Alberto],
Multiple Future Prediction Leveraging Synthetic Trajectories,
ICPR21(6081-6088)
IEEE DOI 2105
Training, Predictive models, Markov processes, Data models, Trajectory, Safety, Planning BibRef

Hu, Q.Y.[Qi-Yang], Wälchli, A.[Adrian], Portenier, T.[Tiziano], Zwicker, M.[Matthias], Favaro, P.[Paolo],
Learning to Take Directions One Step at a Time,
ICPR21(739-746)
IEEE DOI 2105
Training, Tracking, Video sequences, Rendering (computer graphics), Animation, Trajectory BibRef

Amirian, J.[Javad], Zhang, B.Q.[Bing-Qing], Castro, F.V.[Francisco Valente], Baldelomar, J.J.[Juan José], Hayet, J.B.[Jean-Bernard], Pettré, J.[Julien],
Opentraj: Assessing Prediction Complexity in Human Trajectories Datasets,
ACCV20(VI:566-582).
Springer DOI 2103
BibRef

Sun, J.[Jin], Averbuch-Elor, H.[Hadar], Wang, Q.Q.[Qian-Qian], Snavely, N.[Noah],
Hidden Footprints: Learning Contextual Walkability from 3d Human Trails,
ECCV20(XVIII:192-207).
Springer DOI 2012
BibRef

Wang, L.M.[Li-Min], Tong, Z.[Zhan], Ji, B.[Bin], Wu, G.S.[Gang-Shan],
TDN: Temporal Difference Networks for Efficient Action Recognition,
CVPR21(1895-1904)
IEEE DOI 2111
Analytical models, Visualization, Solid modeling, Convolution, Computational modeling, Motion segmentation BibRef

Li, Y.X.[Yi-Xuan], Wang, Z.X.[Zi-Xu], Wang, L.M.[Li-Min], Wu, G.S.[Gang-Shan],
Actions as Moving Points,
ECCV20(XVI: 68-84).
Springer DOI 2010
BibRef

Malla, S., Dariush, B., Choi, C.,
TITAN: Future Forecast Using Action Priors,
CVPR20(11183-11193)
IEEE DOI 2008
Trajectory, Predictive models, Context modeling, Navigation, Roads, Prediction algorithms BibRef

Phan-Minh, T., Grigore, E.C., Boulton, F.A., Beijbom, O., Wolff, E.M.,
CoverNet: Multimodal Behavior Prediction Using Trajectory Sets,
CVPR20(14062-14071)
IEEE DOI 2008
Trajectory, Vehicle dynamics, Probabilistic logic, Uncertainty, Stochastic processes, Standards, Dynamics BibRef

Zhao, T.Y.[Tian-Yang], Xu, Y.F.[Yi-Fei], Monfort, M.[Mathew], Choi, W.G.[Won-Gun], Baker, C.[Chris], Zhao, Y.B.[Yi-Biao], Wang, Y.Z.[Yi-Zhou], Wu, Y.N.[Ying Nian],
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction,
CVPR19(12118-12126).
IEEE DOI 2002
BibRef

Liu, J., Xue, C., Wu, C., Dong, Q.,
A Process-oriented Spatiotemporal Clustering Method for Complex Trajectories,
ISSDQ19(1237-1242).
DOI Link 1912
BibRef

Moayedi, A., Abbaspour, R.A., Chehreghan, A.,
A Comparison of Efficiency of The Optimization Approach for Clustering of Trajectories,
SMPR19(737-740).
DOI Link 1912
BibRef

Barata, C., Figueiredo, M.A.T., Marques, J.S.,
Multiple Motion Fields for Multiple Types of Agents,
ICIP19(1287-1291)
IEEE DOI 1910
Surveillance, trajectory analysis, motion fields, hierarchical Markov models BibRef

Duits, R.[Remco], Smets, B.[Bart], Bekkers, E.[Erik], Portegies, J.[Jim],
Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations,
SSVM21(27-39).
Springer DOI 2106
BibRef

Duits, R.[Remco], St-Onge, E.[Etienne], Portegies, J.[Jim], Smets, B.[Bart],
Total Variation and Mean Curvature PDEs on the Space of Positions and Orientations,
SSVM19(211-223).
Springer DOI 1909
BibRef

Wu, T.[Ting], Xu, Q.[Qing], Li, Y.H.[Yun-He], Guo, Y.J.[Yue-Jun], Schoeffmann, K.[Klaus],
Detail-Preserving Trajectory Summarization Based on Segmentation and Group-Based Filtering,
MMMod19(II:402-413).
Springer DOI 1901
BibRef

Yoon, J.S., Li, Z., Park, H.S.,
3D Semantic Trajectory Reconstruction from 3D Pixel Continuum,
CVPR18(5060-5069)
IEEE DOI 1812
Trajectory, Semantics, Cameras, Image reconstruction, Streaming media BibRef

Wang, W., Lin, Y., Cheng, H., Huang, C.,
Clustering Trajectories in Heterogeneous Representations for Video Event Detection,
ICIP18(933-937)
IEEE DOI 1809
Trajectory, Acceleration, Entropy, Feature extraction, Event detection, Clustering algorithms, trajectory clustering BibRef

Tian, J., Chen, L., Liu, X.,
Movement Classification in Video Using Kinematics-Driven Change Detection and Local Kinematics Shape Pattern,
ICIP18(714-718)
IEEE DOI 1809
Kinematics, Feature extraction, Shape, Shape measurement, Histograms, Muscles, Spatiotemporal phenomena, movement change detection, local kinematics shape pattern BibRef

Wang, Y., Tran, V.Q., Nguyen, M.H.,
Eigen-Evolution Dense Trajectory Descriptors,
FG18(473-479)
IEEE DOI 1806
Clutter, Covariance matrices, Feature extraction, Histograms, Machine learning, Trajectory, Visualization, Action Recognition, Trajectory Pooling BibRef

Sharif, M., Alesheikh, A.A.,
Multi-dimensional Pattern Discovery of Trajectories Using Contextual Information,
GeoInfo17(31-36).
DOI Link 1805
BibRef

Zhou, Y., Yu, H., Wang, S.,
Feature sampling strategies for action recognition,
ICIP17(3968-3972)
IEEE DOI 1803
Feature extraction, Histograms, Image edge detection, Proposals, Sampling methods, Streaming media, Trajectory, Action recognition, Video analysis BibRef