计算机科学 ›› 2017, Vol. 44 ›› Issue (3): 300-306.doi: 10.11896/j.issn.1002-137X.2017.03.061
阎刚,屈高超,于明
YAN Gang, QU Gao-chao and YU Ming
摘要： 稀疏表示技术已成功应用于视觉跟踪,但是仍然存在跟踪算法效率低的问题。提出一种基于Haar-like特征的视频跟踪算法,该算法是基于粒子滤波框架的L1-跟踪算法,其特点是运用Haar-like特征及特征块的思想对完备基进行重新构造。将正负小模板由单个像素改为像素块,降低稀疏表示中过完备基的维数,大幅减少稀疏矩阵的计算量;同时,在保证跟踪质量的前提下适当减少目标模板数量,减少稀疏计算的次数,并控制模板更新频率。实验结果表明,所提算法能大幅提高跟踪的实时性,同时很好地解决了跟踪问题中的短时间遮挡、目标物体的形变以及光照变化等问题。
| [1] MEI X,LING H B.Robust visual tracking using 1 minimization[C]∥2009 IEEE 12th International Conference on Computer Vision.IEEE,2009:1436-1443. [2] WRIGHT J,YANG A Y,GANESH A,et al.Robust Face Reco-gnition via Sparse Representation[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2009,31(2):210-227. [3] ARULAMPALAM M S,MASKELL S,G ORDON N,et al.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Transactions on Signal Processing,2002,50(2):174-188. [4] CANDES E J ,WAKIN M B.An Introduction To Compressive Sampling[J].IEEE Signal Processing Magazine,2008,25(2):21-30. [5] MIE X,LING H B,WU Y,et al.Minimum error bounded efficient 1 tracker with occlusion detection[C]∥2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).IEEE,2011:1257-1264. [6] BAO C L,WU Y,LING H B,et al.Real time robust L1 tracker using accelerated proximal gradient approach[C]∥IEEE Conference on Computer Vision and Pattern Recognition.IEEE Computer Society,2012:1830-1837. [7] JIA X,LU H C,YANG M H.Visual tracking via adaptive structural local sparse appearance model[C]∥IEEE Conference on Computer Vision & Pattern Recognition.2012:1822-1829. [8] ZHONG W,LU H C,YANG M H.Robust object tracking via sparsity-based collaborative model[C]∥IEEE Conference on Computer Vision and Pattern Recognition.IEEE Computer Socie-ty,2012:1838-1845. [9] WANG D,LU H C,YANG M H.Online object tracking with sparse prototypes[J].IEEE Transactions on Image Processing,2013,22(1):314-25. [10] WANG Q,CHEN F,XU W L,et al.Online discriminative object tracking with local sparse representation[C]∥IEEE Workshop on the Applications of Computer Vision.IEEE Computer Society,2012:425-432. [11] BABENKO B,YANG M H,BELONGIE S.Robust ObjectTracking with Online Multiple Instance Learning[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2011,33(8):1619-1632. [12] PAPAGEORGIOU C P ,OREN M,POGGIO T.A Generalframework for object detection[C]∥International Conference on Computer Vision.1998:555-562. [13] WU G X,ZHAO C X,LU W J,et al.Efficient structured 1tracker based on laplacian error distribution[J].International Journal of Machine Learning and Cybernetics August,2015,6(4):581-595. [14] WANG X Y,WANG Y,WAN W G,et al.Object tracking with sparse representation and annealed particle filter[J].Signal Ima-ge and Video Processing,2014,8(6):1053-1068. [15] VIOLA P,JONES M.Rapid Object Detection using a Boosted Cascade of Simple Features[C]∥CVPR 2001.2001:1-511-1-518. [16] ZHOU F,JIANG W,LI S Q,et al.Moving Target Localization and Tracking Algorithms:A Particle Filter Based Method[J].Journal of Software,2014,24(9):2196-2213.(in Chinese) 周帆,江维,李树全,等.基于粒子滤波的移动物体定位和追踪算法[J].软件学报,2013,4(9):2196-2213. [17] TSENG P.Approximation accuracy,gradient methods,and error bound for structured convex optimization[J].Mathematical Programming,2010,125(2):263-295. [18] ZHANG K,ZHANG L,YANG M H.Real-Time CompressiveTracking[C]∥European Conference on Computer Vision.Springer-Verlag,2012:864-877. [19] YILMAZ A,JAVED O,SHAH M.Object tracking:A survey[J].ACM Computing Surveys,2006,38(4):81-93. [20] MEI X,LING H B,WU Y,et al.Efficient minimum errorbounded particle resampling L1 tracker with occlusion detection[J].IEEE Transactions on Image Processing,2013,22(7):2661-2675. |
| No related articles found! |
|
||
首页