Takemura H, Zentaro N, Mizoguchi H. Development of vision based person following module for mobile robots in/out door environment. In: Proceedings of the 2009 IEEE International Conference on Robotics and Biomimetics. Guilin, China: IEEE, 2009. 1675-1680
[2]
Bellotto N, Hu H. Multimodal perception and recognition of humans with a mobile service robot. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics. Piscataway, USA: IEEE, 2008. 401-406
[3]
Quadah N, Cadenat V, Lerasle F, Hamerlain M, Germa T, Boudjema F. Multi-sensor-based control strategy for initiating and maintaining interaction between a robot and a human. Advanced Robotics, 2011, 25(9-10): 1249-1270
[4]
Choi W, Pantofaru C, Silvio S. A general framework for tracking multiple people from a moving camera. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(7): 1577-1591
[5]
Mekonnen A A, Lerasle F, Herbulot A. Cooperative passers-by tracking with a mobile robot and external cameras. Computer Vision and Image Understanding, 2013, 117(10): 1229-1244
[6]
Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using mean shift. In: Proceedings of the 2000 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Hilton Head Island, SC, USA: IEEE, 2000. 142-149
[7]
Liu X M, Yu T. Gradient feature selection for online boosting. In: Proceedings of the 11th IEEE International Conference on Computer Vision. Rio de Janeiro, USA: IEEE, 2007. 1-8
[8]
Collins R T, Liu Y X, Leordeanu M. Online selection of discriminative tracking features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10): 1631-1643
[9]
Zhang K H, Zhang L, Yang M H. Real-time compressive tracking. In: Proceedings of the 2012 European Conference on Computer Vision, Berlin, Heidelberg: Springer-Verlag, 2012. 866-879
[10]
Zhang K H, Song H H. Real-time visual tracking via online weighted multiple instance learning. Pattern Recognition, 2013, 46(1): 397-411
[11]
Ding Jian-Rui, Huang Jian-Hua, Liu Jia-Feng, Zhang Ying-Tao. Combining local features and multi-instance learning for ultrasound image classification. Acta Automatica Sinica, 2013, 39(6): 861-867(丁建睿, 黄碱化, 刘家锋, 张英涛. 局部特征与多示例学习结合的超声图像分类方法. 自动化学报, 2013, 39(6): 861-867
[12]
Satake J, Miura J. Stereo-based multi-person tracking using overlapping silhouette templates. In: Proceedings of the 20th International Conference on Pattern Recognition. Istanbul: IEEE, 2010. 4304-4307
[13]
Takashi Y, Nishiyama M, Sonoura T, Nakamoto H, Tokura S, Sato H, Ozaki F, Matsuhira N, Mizoguchi H. Development of a person following robot with vision based target detection. In: Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, China: IEEE, 2006. 5286-5291
[14]
Yun W H, Kim D, Lee J. Person following with obstacle avoidance based on multi-layered mean shift and force field method. In: Proceedings of the 2010 IEEE International Conference on Systems. Istanbul: IEEE, 2010. 3813-3816
[15]
Martínez-Otzeta J M, Ibarguren A, Ansuategi A, Tubío C, Aristondo J. People following behaviour in an industrial environment using laser and stereo camera. In: Proceedings of the 23rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems. Berlin, Heidelberg: Springer-Verlag, 2010. 508-517
[16]
Andreas E, Bastian L, Konrad S, Luc van G. Robust multiperson tracking from a mobile platform. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(10): 1831-1846
[17]
Babenko B, Yang M H, Belongie S. Robust object tracking with online multiple instance learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1619-1632
[18]
Wang Meng, Dai Ya-Ping, Wang Qing-Lin. A novel FAST-Snake object tracking approach. Acta Automatica Sinica, 2014, 40(6): 1108-1115 (王蒙, 戴亚平, 王庆林. 一种新的FAST-Snake目标跟踪方法. 自动化学报, 2014, 40(6): 1108-1115)
[19]
Adam A, Rivlin E, Shimshoni I. Robust fragments-based tracking using the integral histogram. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Washington D.C., USA: IEEE, 2006. 798-805
[20]
Avidan S. Ensemble tracking. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 494-501
[21]
Grabner H, Grabner M, Bischof H. Real-time tracking via on-line boosting. In: Proceedings of the 17th British Machine Vision Conference. Guildford: BMVA Press, 2006. 47-56
[22]
Grabner H, Leistner C, Bischof H. Semi-supervised on-line boosting for robust tracking. In: Proceedings of the 10th European Conference on Computer Vision. Berlin, Heidelberg: Springer-Verlag, 2008. 234-247
[23]
Liu Yu, Zhu Zhi-Yuan, Guan Qiang, Yang Yi-Ping. Research on experimental-design-based RFID application combinatorial testing optimization. Acta Automatica Sinica 2010, 36(12): 1674-1680(刘禹, 朱智源, 关强, 杨一平. 基于试验设计的RFID应用组合测试优化研究. 自动化学报, 2010, 36(12): 1674-1680)
[24]
Su Lian-Cheng, Zhu Feng. Design of a novel omnidirectional stereo vision system. Acta Automatica Sinica, 2006, 32(1): 67-72(苏连成, 朱枫. 一种新的全向立体视觉系统的设计. 自动化学报, 2006, 32(1): 62-72)
[25]
Jia S M, Sheng J B, Takase K. Obstacle recognition for a service mobile robot based on RFID with multi-antenna and stereo vision. In: Proceedings of the 2008 IEEE International Conference on Information and Automation. Changsha, China: IEEE, 2008. 125-130
[26]
Zhang Juan, Pan Jian-Shou, Wu Ya-Peng, Liu Ji-Yan. Tracking and measurement of moving object in binocular stereo vision. Computer Engineering and Application, 2009, 45(25): 191-194(张娟, 潘建寿, 吴亚鹏, 刘继艳. 基于双目视觉的运动目标跟踪与测量. 计算机工程与应用, 2009, 45(25): 191-194)
[27]
Jia S M, Wang S, Wang L J, Li X Z. Robust human detecting and tracking using varying scale template matching. In: Proceedings of the 2012 IEEE International Conference on Information and Automation. Shenyang, China: IEEE, 2012. 25-30
