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面向视频监控的自动行人检测 被引量:3

Automatic Pedestrian Detection Based on Video Surveillance
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摘要 为了解决目前行人检测技术的检测速度和准确性之间的平衡问题,对基于视频的行人检测技术进行了研究,提出了利用LUV颜色空间信息与C4行人检测算法相结合的视频自动行人检测方法(LUVC4)。首先利用C4行人检测算法快速遍历视频的每帧图像,当得到的窗口置信度在可疑区间时,再进一步对该窗口做LUV颜色空间检测。如果两次检测的加权和分数满足阈值,则判别为行人。通过大量实验表明,该方法在检测速度几乎能达到C4速度的同时,还能在FPPI为0.1时降低约9%的漏检率。 To address the problem that the technologies of pedestrian detection can't achieve the balance between detecting speed and accuracy,this paper aimed to research on pedestrian detection under video surveillance An automatic video pedestrian detection method (denoted as LUVC4) was proposed by combining LUV color space information and C4 pedestrian detection algorithm.Firstly the C4 algorithm is used to rapidly traversal each frame of the video image.The LUV color space is taken to detect this window further when the confidence score of detect window is in the suspicious interval.If the weighted sum of scores of the two detections satisfies the threshold,it is discriminated as a pedestrian.A large number of experiments show that the detection speed of the proposed method nearly reaches that of C4 and it can greatly decrease the missrate about 9 % when false positive per image equals to 0.1.
出处 《计算机科学》 CSCD 北大核心 2014年第12期264-268,共5页 Computer Science
基金 国家自然科学基金(61202191) 中央高校基本科研业务费专项资金(SWJTU12CX095)资助
关键词 行人检测 LUV C4 置信度 Pedestrian detection LUV C4 Confidence score
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参考文献13

  • 1Tsarkov D. Horrocks L Optirnised Classification for Taxonomic Knowledge Bases[C]//Proceedings of the 2005 International Description Logic Workshop(DL 2005). Manchester, UK, 2005.
  • 2王海龙,马宗民,严丽,程经纬.支持模糊数据类型表示的模糊描述逻辑F-SHOIQ(G)[J].计算机学报,2009,32(8):1511-1524. 被引量:11
  • 3程经纬,马宗民,严丽,张富.模糊描述逻辑知识库查询蕴涵的判定方法[J].计算机学报,2012,35(4):767-785. 被引量:2
  • 4Stoilos G,Stamou G,Pan J. Fuzzy Extensions of OWI.: Logical Properties and Reduction to Fuzzy Description Logics[J]. Inter- national Journal of Approximate Reasoning, 2010,51 (6) : 656- 679.
  • 5Stoilos G,Stamou G. Reasoning with fuzzy extensions of OWL and OWL 2[J]. Knowledge and Information Systems, 2013,40 (1) :205-242.
  • 6Bobillo F, Delgado M, G6mez-Romero J. DeLorean: A reasoner for fuzzy OWL 2[J]. Expert Systems with Applications, 2012, 39:258-272.
  • 7李言辉,徐宝文,陆建江,康达周.支持数量约束的扩展模糊描述逻辑复杂性研究[J].软件学报,2006,17(5):968-975. 被引量:19
  • 8邓志鸿,唐世渭,张铭,杨冬青,陈捷.Ontology研究综述[J].北京大学学报(自然科学版),2002,38(5):730-738. 被引量:765
  • 9石莲,孙吉贵.描述逻辑综述[J].计算机科学,2006,33(1):194-197. 被引量:42
  • 10Tsarkov D, HorrocksI. FACT+ + Description Logic Reasoner: System Description[C]//Proceedings of the International Joint Conference on Automated Reasoning ( IJCAR' 06 ). 2006 : 292- 297.

二级参考文献82

  • 1史忠植,蒋运承,张海俊,董明楷.基于描述逻辑的主体服务匹配[J].计算机学报,2004,27(5):625-635. 被引量:62
  • 2刘亚彬,陈岗.基于描述逻辑的空间推理研究[J].计算机科学,2004,31(8):110-112. 被引量:3
  • 3李言辉,徐宝文,陆建江,康达周.支持数量约束的扩展模糊描述逻辑复杂性研究[J].软件学报,2006,17(5):968-975. 被引量:19
  • 4蒋运承,史忠植,汤庸,王驹.面向语义Web语义表示的模糊描述逻辑[J].软件学报,2007,18(6):1257-1269. 被引量:36
  • 5Description Logic. home page http://dl.kr.org/.
  • 6Baader F, Nutt W. Basic Description Logics. In: Baader F, McGuinness, Nardi D, et al. eds. The Description Logic Handbook, Chapter2. Cambridge Univ Press,2003.
  • 7De Giacomo G, Lenzerini M. TBox and ABox Reasoning in Expressive Description Logics. KR 1996. 316-327.
  • 8Brachman R J, Levesque H J. The tractability of subsumption in frame-based description languages. In:Proceedings of the 4th National Conference of the American Association for Artificial Intelligence (AAAIr84) ,Austin, TX, 1984. 34-37.
  • 9Baader F, Horrocks I, Sattler U. Description logics as ontology languages for the semantic web. In: Hutter D, Stephan W, eds.Festschrift in honor of Jorg Siekmann, Lecture Notes in Artificial Intelligence. Springer, 2003.
  • 10Brachman R J, Sehmolze J G. An overview of the KL-ONE knowledge representation system. Cognitive Science, 1985,9 (2) : 171-216.

共引文献821

同被引文献25

  • 1贾慧星,章毓晋.车辆辅助驾驶系统中基于计算机视觉的行人检测研究综述[J].自动化学报,2007,33(1):84-90. 被引量:69
  • 2DOLLAR P,WOJEK C,SCHIELE B,et al.Pedestrian detection:an evaluation of the state of the art[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(4):743-761.
  • 3REILLY V,SOLMAZ B,SHAH M.Shadow Casting Out Of Plane(SCOOP) candidates for human and vehicle detection in aerial imagery[J].International Journal of Computer Vision,2013,101(2):350-366.
  • 4ANDRILUKA M,SCHNITZSPAN P,MEYER J,et al.Vision based victim detection from unmanned aerial vehicles[C]//Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems.Piscataway:IEEE,2010:1740-1747.
  • 5DALAL N,TRIGGS B.Histograms of oriented gradients for human detection[C]//CVPR 2005:Proceedings of the 2005 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE,2005,1:886-893.
  • 6MU Y,YAN S,LIU Y,et al.Discriminative local binary patterns for human detection in personal album[C]//CVPR 2008:Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE,2008:1-8.
  • 7WALK S,MAJER N,SCHINDLER K,et al.New features and insights for pedestrian detection[C]//CVPR 2010:Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE,2010:1030-1037.
  • 8WU J,GEYER C,REHG J.Real-time human detection using contour cues[C]//Proceedings of the 2011 IEEE International Conference on Robotics and Automation.Piscataway:IEEE,2011:860-867.
  • 9TAKACS G,CHANDRASEKHAR V,TSAI S,et al.Unified real-time tracking and recognition with rotation-invariant fast features[C]//Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE,2010:934-941.
  • 10CHANDRASEKHAR V,TAKACS G,TSAI S,et al.CHoG:Compressed histogram of gradients A low bit-rate feature descriptor[C]//Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE,2009:2504-2511.

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