Journal of System Simulation ›› 2017, Vol. 29 ›› Issue (9): 2053-2058.doi: 10.16182/j.issn1004731x.joss.201709023
Previous Articles Next Articles
Xu Peizhen, Yu Zhibin, Jin Weidong, Jiang Haiying
Received:
2017-05-20
Published:
2020-06-02
CLC Number:
Xu Peizhen, Yu Zhibin, Jin Weidong, Jiang Haiying. Action Recognition by Improved Dense Trajectories[J]. Journal of System Simulation, 2017, 29(9): 2053-2058.
[1] Zhu J, Zhao Y, Tang J.Automatic Recognition of Radar Signals Based on Time-frequency Image Character[J]. Defence Science Journal (S0011-748X), 2013, 63(3): 1-6. [2] Wang H, Klaser A, Schmid C, et al.Action Recognition by Dense Trajectories[C]// Proceeding of the 2011 IEEE Conference on Computer Vision and Pattern Recognition. USA: IEEE Computer Society, 2011: 3169-3176. [3] Aggarwal J K.Recognition of Human Activities[M]// Combinatorial Image Analysis. Berlin, Heidelberg, Germany: Springer, 2011: 1-4. [4] Laptev I, Lindeberg T.On Space-Time Interest Points[J]. International Journal of Computer Vision (S0920-5691), 2005, 64(2/3): 107-123. [5] Dollar P, Rabaud V, Cottrell G, et al.Behavior Recognition Via Sparse Spatio-temporal Features[C]// 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance. USA: IEEE Computer Society, 2005: 65-72. [6] Messing R, Pal C, Kautz H.Activity Recognition Using the Velocity Histories of Tracked Keypoints[C]// Proceedings IEEE International Conference on Computer Vision. USA: IEEE, 2009: 104-111. [7] Matikainen P, Hebert M, Sukthankar. Trajectons: Action Recognition Through the Motion Analysis of Tracked Features[C]// Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on. USA: IEEE, 2009: 514-521. [8] Wang H, Klaser A, Schmid C, et al.Dense Trajectories and Motion Boundary Descriptors for Action Recognition[J]. International Journal of Computer Vision (S0920-5691), 2013, 103(1): 60-78. [9] Szeliski R.Image Alignment and Stitching: a Tutorial[J]. Foundations & Trends in Computer Graphics & Vision (S1572-2740), 2004, 2(1): 101-104. [10] Bay H, Tuytelaars T, Gool L V.SURF: Speeded Up Robust Features[J]. Computer Vision & Image Understanding (S1077-3142), 2006, 110(3): 404-417. [11] Gaidon A, Harchaoui Z, Schmid C.Recognizing Activities with Cluster-trees of Track lets [C]// British Machine Vision Conference. United Kingdom: BNVA Press, 2012: 1-6. [12] Farneback G.Two-frame motion estimation based on polynomial expansion[C]// Scandinavian Conference on Image Analysis. Germany: Springer-Verlag, 2003: 363-370. [13] Shi J, Tomasi C.Good Features to Track[M]. USA: Cornell University, 1993. [14] Fischler M A, Bolles R C.Rand on Sample Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography[J]. Communications of the ACM (S0001-0782), 1981, 24(6): 381-395. [15] Wang H, Kläser A, Schmid C, et al.Dense Trajectories and Motion Boundary Descriptors for Action Recognition[J]. International Journal of Computer Vision (S0920-5691), 2013, 103(1): 60-79. [16] Prest A, Schmid C, Ferrari V.Weakly supervised learning of interactions between humans and objects[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence (S0162-8828), 2012, 34(3): 601-614. [17] Watanabe T, Ito S, Yokoi K.Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection[M]// Advances in Image and Video Technology. Berlin Heidelberg, Germany: Springer, 2009: 37-47. [18] Peng X, Qiao Y, Peng Q, et al.Exploring Motion Boundary based Sampling and Spatial-Temporal Context Descriptors for Action Recognition[C]// British Machine Vision Conference. United Kingdom: BMVC, 2013: 1-11. [19] Farneback G.Two-frame motion estimation based on polynomial expansion[C]// Scandinavian Conference on Image Analysis. Germany: Springer-Verlag, 2003: 363-370. [20] Wang H, Klaser A, Schmid C, et al.Dense Trajectories and Motion Boundary Descriptors for Action Recognition[J]. International Journal of Computer Vision (S0920-5691), 2013, 103(1): 60-79. [21] Zhou Z H, Zhang M L.Neural Networks for Multi Instance Learning [R]// International Conference on Intelligent Information Technology. China: Nanjing University, 2002: 1-14. [22] Ryoo M S, Aggarwal J K.Spatio-temporal Relationship Match: Video Structure Comparison for Recognition of Complex Human Activities[C]// IEEE, International Conference on Computer Vision. USA: IEEE Xplore, 2009: 1593-1600. [23] Alonso P P, Marcin M, Ian R, et al.Structured Learning of Human Interactions in TV Shows[J]. IEEE Transactions on Software Engineering (S0098-5589), 2012, 34(12): 2441-2453. [24] Yang L, Gao C, Meng D, et al.A Novel Groups parsity-Optimization-Based Feature Selection Model for Complex Interaction Recognition [M]// Computer Vision-ACCV2014. Germany: Springer International Publishing, 2015: 508-521. |
[1] | Zhijie Li, Haoqi Shi, Changhua Li, Jie Zhang. Image Center Layout Optimization Method Based on Improved Genetic Algorithm [J]. Journal of System Simulation, 2022, 34(6): 1173-1184. |
[2] | Miaojia Lu, Chengyuan Huang, Jing Teng. Multi-agent Simulation for Online Fresh Food Autonomous Delivery [J]. Journal of System Simulation, 2022, 34(6): 1185-1195. |
[3] | Bin Chen, Yue Liu, Yalei Yang. Airport Flight Transit Support Time Collaborative Planning Modeling Based on STN [J]. Journal of System Simulation, 2022, 34(6): 1196-1207. |
[4] | Xinyu Dou, Xiaohui Chen, Dequn Liang, Bin Lin. A High Spectral-efficiency Maritime Very-High-Frequency Communication Technology and Simulation [J]. Journal of System Simulation, 2022, 34(6): 1208-1218. |
[5] | Shaomi Duan, Huilong Luo, Haipeng Liu. A Hybrid Algorithm Based on Seeker Optimization Algorithm and Salp Swarm Algorithm for PID Parameters Optimization [J]. Journal of System Simulation, 2022, 34(6): 1230-1246. |
[6] | Kai Yang, Chunyi Chen, Xiaojuan Hu, Haiyang Yu. Denoising Algorithm Based on Multi-feature Non-local Mean Filtering for Monte Carlo Rendered Images [J]. Journal of System Simulation, 2022, 34(6): 1259-1266. |
[7] | Peipei Zhou, Xinglin Hou. An Unsupervised Deep Neural Network for Image Fusion [J]. Journal of System Simulation, 2022, 34(6): 1267-1274. |
[8] | Qi Chen, Haoyang Cui. Visual inspection model of UAV cluster based on improved pigeon flock hierarchy [J]. Journal of System Simulation, 2022, 34(6): 1275-1285. |
[9] | Muqing Wang, Lei Zhang, Xiumin Fan, Xiaomeng Luo, Wenmin Zhu. Simulation Method of Virtual Human Pose Optimization Based On VR Peripherals [J]. Journal of System Simulation, 2022, 34(6): 1296-1303. |
[10] | Peng Cheng, Wenzhu Zhang, Shuhan Xie, Zixuan Yang. Research and Simulation of Internet of Vehicles Task Offloading Based on Mobile Edge Computing [J]. Journal of System Simulation, 2022, 34(6): 1304-1311. |
[11] | Cheng Lu, Xuesheng Jin. Design of Interactive Simulated Water Gun Fire Fighting Training System Based on Steam VR [J]. Journal of System Simulation, 2022, 34(6): 1312-1319. |
[12] | Hongnai Gao, Lijiang Fu, Qian Xia, Ya Guo. Application of Observability in Performance Evaluation of Photosynthesis Model [J]. Journal of System Simulation, 2022, 34(6): 1330-1342. |
[13] | Lingjia Ni, Xiaoxia Huang, Hongga Li, Zibo Zhang. Research on Fire Emergency Evacuation Simulation Based on Cooperative Deep Reinforcement Learning [J]. Journal of System Simulation, 2022, 34(6): 1353-1366. |
[14] | Yiling Sun, Yi Chen, Guihua Shan, Xiaoxing Li. Multi-person Interactive Globe System Based on AR Technology [J]. Journal of System Simulation, 2022, 34(6): 1367-1374. |
[15] | Dun Meng, Zhuo Hu, Huajun Zhang. Simulation of Multi-layer Ship Evacuation System Based on Improved A* Algorithm [J]. Journal of System Simulation, 2022, 34(6): 1375-1382. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||