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基于凸包裁剪的行人视频检测算法 被引量:6

Pedestrian Video Detection Algorithm Based on Convex Hull Clipping
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摘要 为了解决行人群体视频检测的难题,提出一种基于凸包裁剪的行人视频检测算法。该算法采用局部凸包技术搜索行人外部轮廓,利用凹点挖掘技术裁剪轮廓曲线,建立相应规则排除非头部线段,通过最小二乘拟合法对头部曲线进行快速椭圆检测。实验结果表明,该算法能准确地检测出重叠或连通的头部,排除非头部物体,且处理速度快,实际应用价值高。 This paper proposes a pedestrian video detection algorithm based on convex hull clipping in order to solve the problem of pedestrian crowd video detection. The algorithm uses part convex hull technology to search pedestrian outlines,clips out contour curves of pedestrians by using concave points mining technology. It gets rid of non-head curves in clipped lines depending on rules,fast ellipse detection based on least square. Experimental results indicate that this algorithm can exactly detect overlap or connected heads and exclude non-head objects,and it has fast processing speed,high practical application value.
作者 李江 孙立军
出处 《计算机工程》 CAS CSCD 北大核心 2010年第2期173-175,共3页 Computer Engineering
基金 国家"十一五"科技支撑计划基金资助项目(06dz12001) 上海市科委创新行动计划基金资助项目(07dz12006)
关键词 凸包 凹点挖掘 行人检测 convex hull concave point mining pedestrian detection
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  • 1李良福,冯祖仁,贺凯良.一种基于随机Hough变换的椭圆检测算法研究[J].模式识别与人工智能,2005,18(4):459-464. 被引量:15
  • 2黎自强,滕弘飞.广义Hough变换:多个圆的快速随机检测[J].计算机辅助设计与图形学学报,2006,18(1):27-33. 被引量:40
  • 3Liang Ji.Intelligent splitting in the chromo some domain[J].Pattern Recognition, 1989,22(5): 519-532.
  • 4Castleman K R.Digital image processing[M].[S.l.]:Prentice Hall, 1996.
  • 5Khurana S S,Barycenters.Pinnacle points and denting points[J]. Trans Ams, 1973,180 : 497-503.
  • 6吕林根 许子道.解析几何[M].北京:高等教育出版社,1987..
  • 7Yuen H K, Illingwoth J, Kitter J. Detecting partially occluded ellipses using the hough transform[J]. Image Vision and computing, 1989, 7(1):31-37.
  • 8Loannou, D Huda, W Laine, et al.Circle recognition through A 2D Hough transform and radius histogram[J]. Image and Vision Computing, 1999,(17):15-26.
  • 9Heung-Soo Kim, Jong-Hwan Kim. A two-step circle detection algorithm from the intersection chords[J]. Pattern Recognition Letters,2001,(22):787-798.
  • 10Peng-Yeng yin. A new circle/ellipse detector using genetic algorithms[J]. Pattern Recognition Letters, 1999,(20):731-740.

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  • 1覃中平,张焕国.多边形的方向与圆弧可视性[J].计算机学报,1994,17(4):257-263. 被引量:9
  • 2刘新,刘任任.一种改进的构建凸包的分治算法[J].计算机工程与科学,2006,28(8):63-65. 被引量:7
  • 3施游,黄少年,张友生.基于交互信息量和联合熵的镜头检测算法[J].计算机工程与应用,2006,42(30):54-56. 被引量:8
  • 4何磊,蒋大为,张永锋,周敏.基于简化多边形类正切空间表示的图形渐变算法[J].计算机辅助设计与图形学学报,2007,19(3):304-310. 被引量:9
  • 5Viola P A, Jones M J. Rapid Object Detection Using a Boosted Cascade of Simple Features[C]//Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Hawaii, USA: IEEE Press, 2001: 511-518.
  • 6Wang Liming, Shi Jianbo, Song Gang, et al. Object Detection Combining Recognition and Segmentation[C]//Proc. of the 8th Asian Conference On Computer Vision. Tokyo, Japan: [s. n.], 2007.
  • 7Liu D, Chen T. Soft Shape Context for Interative Closest Point Registration[C]//Proc. of 2004 International Conference on Image Processing. Singapore: [s. n.], 2004: 1081-1084.
  • 8PASCAL Object Recognition Database Collection[EB/DL]. (2008-11- 05). http://pascallin.ecs.soton.ac,uk/challenges/VOC/databases.html.
  • 9Hanialic A. Shot-boundary Detection: Unraveled and Resolved[J]. IEEE Trans. on Circuits and Systems for Video Technology, 2002, 12(2): 90-105.
  • 10Quenot G M, Moraru D, Besacier L. CLIPS at TRECVID: Shot Boundary Detection and Feature Detection[C] //Proc. of TRECVID’03. Gaithersburg, Maryland, USA: [s. n.] , 2003.

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