• Electronics Optics & Control
  • Vol. 29, Issue 4, 59 (2022)
LIU Wenhui, CHAO Yuan, TANG Hanbing, and XU Peng
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3969/j.issn.1671-637x.2022.04.012 Cite this Article
    LIU Wenhui, CHAO Yuan, TANG Hanbing, XU Peng. A Review on Visual Target Detection and Tracking Methods for Mobile Robot[J]. Electronics Optics & Control, 2022, 29(4): 59 Copy Citation Text show less
    References

    [1] CHEN R.Image segmentation and target tracking based on meanshift algorithm[C]//Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics.Paris:Atlantis Press2015:723-728.

    [2] DANELLJAN MHGER GKHAN F Set al.Accurate scale estimation for robust visual tracking[C]//Proceedings of the British Machine Vision Conference.NottinghamUK:BMVA Press2014:1-11.

    [5] YANG FLU H CYANG M H.Robust superpixel tracking[J].IEEE Transactions on Image Processing201423(4):1639-1651.

    [6] YU QDINH T BMEDIONI G.Online tracking and reacquisition using co-trained generative and discriminative trackers[C]//Proceedings of the 10th European Conference on Computer Vision.Berlin:Springer 2008:678-691.

    [7] WU YCHENG JWANG J Qet al.Real-time probabilistic covariance tracking with efficient model update[J].IEEE Transactions on Image Processing201221(5):2824-2837.

    [8] JEPSON A DFLEET D JEL-MARAGHI T F.Robust online appearance models for visual tracking[J].IEEE Transactions on Pattern Analysis and Machine Intelligence 200325(10):1296-1311.

    [11] HUANG L HMA BSHEN J Bet al.Visual tracking by sampling in part space[J].IEEE Transactions on Image Processing201726(12):5800-5810.

    [12] LUO JFAN Y KJIANG Pet al.Vehicle platform attitude estimation method based on adaptive Kalman filter and sliding window least squares[J].Measurement Science and Technology202132(3):1-9.

    [24] MORIDVAISI HRAZZAZI FPOURMINA M Aet al.An extended KCF tracking algorithm based on TLD structure in low frame rate videos[J].Multimedia Tools and Applications202079:20995-21012.

    [26] KOTSIANTIS S BZAHARAKIS I DPINTELAS P E.Machine learning:a review of classification and combining techniques[J].Artificial Intelligence Review2006 26(3):159-190.

    [27] MESHRAM S BSHINDE S M.A survey on ensemble methods for high dimensional data classification in biomedicine field[J].International Journal of Computer Applications2015111(11):5-7.

    [28] DAZ-SAN MARTN GREYES GONZLEZ LSAINZ-RUIZ Set al.Automatic ankle angle detection by integrated RGB and depth camera system[J].Sensors 202121(5):1909.

    [29] LIU W CJIN GXIE Y Fet al.Broadband high-efficiency polarization-independent double-layer slanted grating for RGB colors[J].Optics Communications2021488:126864.

    [30] HADIPRAKOSO R B.Face anti-spoofing method with blinking eye and HSV texture analysis[J].IOP Conference Series:Materials Science and Engineering2020 1007:012034.

    [31] BARGSHADY GZHOU X JDEO R Cet al.The modeling of human facial pain intensity based on temporal convolutional networks trained with video frames in HSV color space[J].Applied Soft Computing202097(A):106805.

    [32] LOU JWANG HCHEN L Tet al.Exploiting color name space for salient object detection[J].Multimedia Tools and Applications202079:10873-10897.

    [33] TIAN X LJIAO L CLIU X Let al.Feature integration of EODH and Color-SIFT:application to image retrieval based on codebook[J].Signal Processing:Image Communication201429(4):530-545.

    [34] BOSCH AZISSERMAN AMUNOZ X.Scene classification using a hybrid generative/discriminative approach[J].IEEE Transactions on Pattern Analysis and Machine Intelligence200830(4):712-727.

    [35] VAN DE WEIJER JSCHMID C.Coloring local feature extraction[C]//European Conference on Computer Vision (ECCV).Berlin:Springer2006:334-348.

    [37] HARRIS C GSTEPHENS M.A combined corner and edge detector[C]//Proceedings of the Alvey Vision Conference.Manchester:Alvey Vision Club1988:23.1-23.6.

    [38] ROSTEN EDRUMMOND T.Machine learning for high-speed corner detection[C]//European Conference on Computer Vision.Berlin:Springer2006:430-443.

    [41] LOWE D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision200460:91-110.

    [42] DALAL NTRIGGS B.Histograms of oriented gradients for human detection[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San DiegoCA:IEEE2005:886-893.

    [43] ZHANG K PZHANG Z PLI Z Fet al.Joint face detection and alignment using multitask cascaded convolutional networks[J].IEEE Signal Processing Letters 201623(10):1499-1503.

    [44] KE YSUKTHANKAR R.PCA-SIFT:a more distinctive representation for local image descriptors[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.WashingtonD.C.:IEEE2004:II-506-II-513.

    [45] ZHANG XHONG S GNING A Pet al.Pedestrian detection with EDGE features of color image and HOG on depth images[J].Automatic Control and Computer Sciences202054:168-178.

    [46] WATANABE TITO SYOKOI K.Co-occurrence histograms of oriented gradients for human detection[C]//Pacific-Rim Symposium on Image and Video Technology.Berlin:Springer2009:37-47.

    [47] JAIN A KRATHA N KLAKSHMANAN S.Object detection using Gabor filters[J].Pattern Recognition1997 30(2):295-309.

    [48] AHONEN THADID APIETIKINEN M.Face recognition with local binary patterns[C]//European Conference on Computer Vision (ECCV).Berlin:Springer 2004:469-481.

    [49] LIENHART RMAYDT J.An extended set of Haar-like features for rapid object detection[C]//Proceedings of International Conference on Image Processing.RochesterNY:IEEE2002:22-25.

    [50] VIOLA PJONES M J.Robust real-time object detection[R].CambridgeMass:Compaq Computer Corporation 2001.

    [51] GOODFELLOW IBENGIO YCOURVILLE A.Deep learning[M].Cambridge: MIT Press2016.

    [52] GU J XWANG Z HKUEN Jet al.Recent advances in convolutional neural networks[J].Pattern Recognition 201877:354-377.

    [53] LECUN YBOSER BDENKER J Set al.Backpropagation applied to handwritten zip code recognition[J].Neural Computation19891:541-551.

    [54] KRIZHEVSKY ASUTSKEVER IHINTON G E.ImageNet classification with deep convolutional neural networks[C]//Proceedings of the 25th International Conference on Neural Information Processing Systems.Red HookNY:Curran Associates Inc.2012:1097-1105.

    [55] GIRSHICK RDONAHUE JDARRELL Tet al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]//IEEE Conference on Computer Vision and Pattern Recognition.ColumbusOH:IEEE2014:580-587.

    [56] GIRSHICK R.Fast R-CNN[C]//IEEE International Conference on Computer Vision (ICCV).Santiago:IEEE 2015:1440-1448.

    [57] REN S QHE K MGIRSHICK Ret al.Faster R-CNN:towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence201739(6):1137-1149.

    [59] CARRANZA-GARCA MLARA-BENTEZ PGARCA-GUTIRREZ Jet al.Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance[J].Neurocomputing2021 449:229-244.

    [60] REDMON JDIVVALA SGIRSHICK Ret al.You only look once:unifiedreal-time object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Las VegasNV:IEEE2016:779-788.

    [61] LIU WANGUELOV DERHAN Det al.SSD:single shot multibox detector[C]//European Conference on Computer Vision.Cham:Springer2016:21-37.

    [62] REDMON JFARHADI A.YOLO9000:betterfasterstronger[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR).HonoluluHI:IEEE2017:6517-6525.

    [63] XUE Y JJU Z Y.Multiple pedestrian tracking under first-person perspective using deep neural network and social force optimization[J].Optik2021240:166981.

    [64] ZAGHARI NFATHY MJAMEII S Met al.The improvement in obstacle detection in autonomous vehicles using YOLO non-maximum suppression fuzzy algorithm[J].The Journal of Supercomputing202177:13421-13446.

    [67] MNIH VKAVUKCUOGLU KSILVER D.et al.Human-level control through deep reinforcement learning[J].Nature2015518:529-533.

    [68] MNIH VKAVUKCUOGLU KSILVER Det al.Playing Atari with deep reinforcement learning[EB/OL].(2013-12-19)[2021-06-21].https://arxiv.org/abs/1312.5602v1.

    [69] SHI J BTOMASI C.Good features to track[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.SeattleWA:IEEE1994:593-600.

    [70] DU KJU Y FJIN Y Let al.Object tracking based on improved MeanShift and SIFT[C]//The 2nd International Conference on Consumer ElectronicsCommunications and Networks.Yichang:IEEE2012:2716-2719.

    [71] EXNER DBRUNS EKURZ Det al.Fast and robust CAMShift tracking[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San FranciscoCA:IEEE2010:9-16.

    [73] YUAN B HZHANG D XFU Ket al.Video tracking of human with occlusion based on MeanShift and Kalman filter[J].Applied Mechanics and Materials2012380-384:3672-3677.

    [74] ABHARI S QERSHADI T Z.Target tracking based on mean shift and Kalman filter with kernel histogram filtering[J].Computer and Information Science20114(2):152-160.

    [75] CAMPLANI MPAIEMENT AMIRMEHDI Met al.Multiple human tracking in RGB-depth data:a survey[J].IET Computer Vision201711(4):265-285.

    [78] MEI XLING H B.Robust visual tracking using l1 minimization[C]//IEEE 12th International Conference on Computer Vision.Kyoto:IEEE2009:1436-1443.

    [79] MEI XLING H BWU Yet al.Efficient minimum error bounded particle resampling L1 tracker with occlusion detection[J].IEEE Transactions on Image Processing201322(7):2661-2675.

    [81] BOLME D SBEVERIDGE J RDRAPER B Aet al.Visual object tracking using adaptive correlation filters[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San FranciscoCA:IEEE 2010:2544-2550.

    [82] 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(3):583-596.

    [83] DANELLJAN MROBINSON AKHAN F Set al.Beyond correlation filters:learning continuous convolution operators for visual tracking[C]//European Conference on Computer Vision (ECCV).Cham:Springer2016:472-488.

    [84] DANELLJAN MBHAT GKHAN F Set al.ECO:efficient convolution operators for tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR).HonoluluHI:IEEE2017:6931-6939.

    [85] WANG N YYEUNG D Y.Learning a deep compact image representation for visual tracking[C]//Proceedings of the 26th International Conference on Neural Information Processing Systems.Red HookNY:Curran Associates Inc.2013:809-817.

    [86] DING J WHUANG Y ZLIU Wet al.Severely blurred object tracking by learning deep image representations[J].IEEE Transactions on Circuits and Systems for Video Technology201626(2):319-331.

    [88] BERTINETTO LVALMADRE JHENRIQUES J Fet al.Fully-convolutional Siamese networks for object tracking[C]//European Conference on Computer Vision (ECCV).Cham:Springer2016:850-865.

    [89] LI BYAN J JWU Wet al.High performance visual tracking with Siamese region proposal network[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition.Salt Lake CityUT:IEEE2018:8971-8980.

    LIU Wenhui, CHAO Yuan, TANG Hanbing, XU Peng. A Review on Visual Target Detection and Tracking Methods for Mobile Robot[J]. Electronics Optics & Control, 2022, 29(4): 59
    Download Citation