期刊文献+

复杂背景下基于图像融合的运动目标轮廓提取算法 被引量:16

Algorithm of extracting moving object silhouette based on frame fusion under complex background
下载PDF
导出
摘要 运动目标轮廓的有效提取对于目标识别、跟踪和行为的理解等后期的处理是非常重要的。受背景复杂性的影响,当背景灰度和运动目标的灰度相近时,提取的运动目标易产生空洞,某些部位无法完全恢复。根据帧差法的基本原理,提出了一种针对复杂背景的运动目标检测、轮廓提取方法。首先,对图像进行滤波处理,采用最大方差比阈值法消除了剩余部分噪声和背景,然后在三帧时间差分法基础上,利用序列中多帧图像融合运动信息,并确定参考区域,通过对原图像进行回扫描,最终提取出完整的运动目标轮廓。实验结果验证了算法的稳健性和有效性。 Effective extraction of the moving object silhouette is essential for the subsequent processing, including target identification, tracking, behavior comprehension, and so on, In some cases, especially when there is low contrast in gray between the background and moving object, the recovered-object is often made up of holes and distorted parts. To improve the performance of extraction in such situation, a modified method based on the principle of frames subtraction was presented. Firstly pre-filtering was needed to alleviate the Gauss noise. Secondly, a maximum variance ratio threshold value was used to remove the remaining noise and background. Then some frames were fused to obtain more information about the moving object, and an area for reference was defined at the same time. After scanning the original image, the moving object silhouette was recovered. Experiment results prove that the modified method is more robust, and superior to other traditional ones.
出处 《计算机应用》 CSCD 北大核心 2006年第1期123-126,共4页 journal of Computer Applications
关键词 运动目标 复杂背景 帧差法 多帧图像融合 低对比度 moving object complicated background frame subtraction frames fusion low-contrast
  • 引文网络
  • 相关文献

参考文献8

  • 1STAUFFER C, GRIMSON W. Adaptive background mixture models for real-time tracking[A]. Proc IEEE Conference on Computer Vision and Pattern Recognition[C]. Fort Collins, Colorado, 1999. 246- 252.
  • 2HARTAOHU I, HARWOOD D, DAVIS L. W4: Real-time surveillance of people and their activities[J]. IEEE Trans Pattern Analysis and Ma2 chine Intelligence, 2000, 22(8) : 809 - 830,.
  • 3MEYER D, DENZLE J, NIEMANN H. Model based extraction of articulated objects in image sequences for gait analysis[A]. Proc IEEE Inter2 national Conference on Image Processing[C]. Santa Barbara, California, 1997.78 - 81.
  • 4王亮,胡卫明,谭铁牛.人运动的视觉分析综述[J].计算机学报,2002,25(3):225-237. 被引量:276
  • 5LIPTON A, FUJIYOSHI H, PATIL R. Moving target classification and tracking from real-time video[A]. Proc IEEE Workshop on Application of Computer Vision[C]. Princeton, NJ, 1998.8 - 14.
  • 6ANDERSON C, BERT P, VANDER WG. Change detection and tracking using pyramids transformation techniques[A]. Proc SPIE Conference on intelligence Robots and Computer Vision[C]. Cambridge, MA, 1985,579.72-78.
  • 7DUBMISSION MP, JAIN AK. Contour extraction of moving objects in complex outdoor scenes[J]. Intematlonal Journal of Computer Vision, 1995, 14(1) : 83 - 105.
  • 8柴本成,柴国钟,姜献锋.一种新的自动阈值图像分割方法[J].机械,2003,30(4):34-35. 被引量:6

二级参考文献114

  • 1[25]Kohle M, Merkl D, Kastner J. Clinical gait analysis by neural networks: Issues and experiences. In: Proc IEEE Symposium on Computer-Based Medical Systems, Maribor, Slovenia, 1997. 138-143
  • 2[26]Meyer D, Denzler J, Niemann H. Model based extraction of articulated objects in image sequences for gait analysis. In: Proc IEEE International Conference on Image Processing, Santa Barbara, California 1997. 78-81
  • 3[27]McKenna S et al. Tracking groups of people. Computer Vision and Image Understanding, 2000, 80(1):42-56
  • 4[28]Karmann K, Brandt A. Moving object recognition using an adaptive background memory. In: Cappellini V ed. Time-varying Image Processing and Moving Object Recognition. 2. Elsevier, Amsterdam, The Netherlands, 1990
  • 5[29]Kilger M. A shadow handler in a video-based real-time traffic monitoring system. In: Proc IEEE Workshop on Applications of Computer Vision, Palm Springs, CA, 1992.1060-1066
  • 6[30]Stauffer C, Grimson W. Adaptive background mixture models for real-time tracking. In: Proc IEEE Conference on Computer Vision and Pattern Recognition, Fort Collins, Colorado, 1999, 2:246-252
  • 7[31]Wren C, Azarbayejani A, Darrell T, Pentland A. Pfinder: Real-time tracking of the human body. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(7):780-785
  • 8[32]Arseneau S, Cooperstock J. Real-time image segmentation for action recognition. In: Proc IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, Canada, 1999. 86-89
  • 9[33]Sun H, Feng T, Tan T. Robust extraction of moving objects from image sequences. In: Proc the Fourth Asian Conference on Computer Vision, Taiwan, 2000.961-964
  • 10[34]Lipton A, Fujiyoshi H, Patil R. Moving target classification and tracking from real-time video. In: Proc IEEE Workshop on Applications of Computer Vision, Princeton, NJ, 1998. 8-14

共引文献280

同被引文献138

引证文献16

二级引证文献89

;
使用帮助 返回顶部