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- 2017
实时鲁棒的频域空间目标跟踪方法
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Abstract:
摘要 本文中实现了一种实时鲁棒的目标跟踪方法，提出了新颖的基于目标形状和外观的稠密循环采样方法、循环矩阵和频域空间的能量最小化目标跟踪方法。本文方法总体上减少了需要处理的数据量，尤其是加入了循环矩阵，极大地简化了计算过程，并将目标特征转换到高维频域空间进行了线性表示，最后用高频空间能量最小化的方法实现了更加快速和精准的目标跟踪。通过大量的对比实验表明，本文方法的总体效果较好，在目标朝向变化、场景光照变化、视频抖动、目标尺度模式变化、目标部分遮挡等环境下，较目前效果最好、最新的方法，本文方法在综合的跟踪精度和效率方面更能取得较好的效果。
Abstract：This paper addresses real-time and robust object tracking method. In this paper, dense circulation sampling and frequency domain transform method were used in target tracking processing. This paper proposed energy minimization object tracking method in frequency domain space and put forward the concept of dense circulation sampling to solve object shape changes, appearance changes, object orientation changes, scene illumination changes, video jitter, objective scale changes and object occlusion problems in tracking processing. This method calculates a target by ten adjacent frames and circulation matrix in frequency domain space. This algorithm defines error as an energy function. This method proposed frequency domain energy minimum method firstly. Energy minimization make error between target and ground truth minimize. This algorithm can obtain more precision target results rapidly, so data quantity is sharp decreased. This algorithm use the dense circulation sampling and energy minimization method to implement a stable visual tracking in such situation as target orientation deformation, scene illumination changes, video stabilization, target scale transformation, target part occlusion. Compared with the latest and the best performance methods at present, the proposed method has significantly improved the tracking precision and efficiency.
| [1] | FIASCHI L,DIEGO F,GREGOR K,et al.Tracking indistinguishable translucent objects over time using weakly supervised structured learning[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2014:2736-2743. |
| [2] | KALAL Z,MIKOLAJCZYK K,MATAS J.Tracking-learning-detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(7):1409-1422. |
| [3] | JIA X,LU H,YANG M H.Visual tracking via adaptive structural local sparse appearance model[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2012:1822-1829. |
| [4] | PATNAIK R.Distortion-invariant kernel correlation lters for general object recognition[D].Pittsburgh:Carnegie Mellon University,2009. |
| [5] | GRABNER H,LEISTNER C,BISCHOF H.Semi-supervised on-line boosting for robust tracking[C]//Proceedings of European Conference on Computer Vision.Berlin:Springer Verlag,2008:234-247. |
| [6] | LI M,MA F,NIAN F.Robust visual tracking via appearance modeling and sparse representation[J].Journal of Computers,2014,9(7):1612-1619. |
| [7] | BROX T,MALIK J.Object segmentation by long term analysis of point trajectories[C]//Proceedings of European Conference on Computer Vision.Berlin:Springer Verlag,2010:282-295. |
| [8] | HONG S,KWAK S,HAN B.Orderless tracking through model-averaged posterior estimation[C]//Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2013:2296-2303. |
| [9] | GU S,ZHENG Y,TOMASI C.Linear time offline tracking and lower envelope algorithms[C]//Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2011:1840-1846. |
| [10] | SUPANCIC J S,RAMANAN D.Self-paced learning for long-term tracking[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Piscataway,NJ:IEEE Press,2013:2379-2386. |
| [11] | WU Y,LIM J,YANG M H.Online object tracking:A benchmark[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2013:2411-2418. |
| [12] | GRABNER H,BISCHOF H.On-line boosting and vision[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2006:260-267. |
| [13] | BABENKO B,YANG M H,BELONGIE S.Visual tracking with online multiple instance learning[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2009:983-990. |
| [14] | HARE S,GOLODETZ S,SAFFARI A,et al.Struck:Structured output tracking with kernels[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,38(10):2096-2109. |
| [15] | ROSS D A,LIM J,LIN R S,et al.Incremental learning for robust visual tracking[J].International Journal of Computer Version,2008,77(1-3):125-141. |
| [16] | MEI X,LING H.Robust visual tracking and vehicle classification via sparse representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(11):2259-2272. |
| [17] | LIU B,HUANG J,KULIKOWSKI C,et al.Robust visual tracking using local sparse appearance model and k-selection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(12):2968-2981. |
| [18] | HUA Y,ALAHARI K,SCHMID C.Occlusion and motion reasoning for long-term tracking[C]//Proceedings of European Conference on Computer Vision.Berlin:Springer Verlag,2014:172-187. |
| [19] | BROX T,MALIK J.Large displacement opticalow:Descriptor matching in variational motion estimation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(3):510-513. |
| [20] | BERCLAZ J,FLEURET F,TURETKEN E,et al.Multiple object tracking using k-shortest paths optimization[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(9):1806-1819. |
| [21] | KWON J,LEEK M.Visual tracking decomposition[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2010:1269-1276. |
| [22] | HAN Z J,YE Q X,JIAO J B.Robust visual object tracking via sparse representation and reconstruction[C]//Proceedings of International Conference on Computer Analysis of Images and Patterns.Berlin:Springer Verlag,2013:282-289. |
| [23] | KALAL Z,MATAS J,MIKOLAJCZYK K.PN learning:Bootstrapping binary classifiers by structural constraints[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2010:49-56. |
| [24] | 石武祯,梅林,王文斐,等.面向复杂场景的局部分布场跟踪方法[J].计算机辅助设计与图形学学报,2014,26(11):2031-2038.SHI W Z,MEI L,WANG W F,et al.Local distribution fields for tracking in complex scenarios[J].Journal of Computer-Aided Design & Computer Graphics,2014,26(11):2031-2038(in Chinese). |
| [25] | ZHANG T,GHANEM B,LIU S,et al.Robust visual tracking via multi-task sparse learning[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2012:2042-2049. |
| [26] | DINH T B,VO N,MEDIONI G.Context tracker:Exploring supporters and distracters in unconstrained environments[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2011:1177-1184. |
| [27] | BOLME D S,BEVERIDGE J R,DRAPER B A,et al.Visual object tracking using adaptive correlation filters[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2011:2544-2550. |
| [28] | HENRIQUES J,CASEIRO R,MARTINS P,et al.Exploiting the circulant structure of tracking-by-detection with kernels[C]//Proceedings of European Conference on Computer Vision.Berlin:Springer Verlag,2012:702-715. |
| [29] | CEHOVIN L,KRISTAN M,LEONARDIS A.Robust visual tracking using an adaptive coupledlayer visual model[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(4):941-953. |
| [30] | BAO C,WU Y,LING H,et al.Real time robust tracker using accelerated proximal gradient approach[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2012:1830-1837. |
| [31] | LIU B,HUANG J,YANG L,et al.Robust tracking using local sparse appearance model and k-selection[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2011:1313-1320. |
| [32] | BABENKO B,YANG M H,BELONGIE S.Robust object tracking with online multiple instance learning[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(8):1619-1632. |
| [33] | ZHANG K,ZHANG L,YANG M H.Real-time compressive tracking[C]//Proceedings of European Conference on Computer Vision.Berlin:Springer Verlag,2012:864-877. |
| [34] | HENRIQUES J F,CASEIRO R,MARTINS P,et al.High-speed tracking with kernelized correlation filters[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2015,37(7):583-596. |
| [35] | SEVILLA-LARA L,LEARNED-MILLER E.Distribution elds for tracking[C]//Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance-AVSS 2015.Piscataway,NJ:IEEE Press,2015:474-479. |
| [36] | KWON J,LEE K M.Tracking by sampling trackers[C]//Proceedings of the IEEE International Conference on Computer Vision,International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2011:1195-1202. |
