박사

안개 영상에서 비가시성 개선 및 객체 추적 = Invisibility Enhancement and Object Tracking in Foggy Image

김상균 2015년
논문상세정보
' 안개 영상에서 비가시성 개선 및 객체 추적 = Invisibility Enhancement and Object Tracking in Foggy Image' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 객체 추적
  • 객체검출
  • 변분법
  • 안개제거
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
144 0

0.0%

' 안개 영상에서 비가시성 개선 및 객체 추적 = Invisibility Enhancement and Object Tracking in Foggy Image' 의 참고문헌

  • “클라우지우스 엔트로피와 적응적 가우 시안 혼합 모델을 이용한 움직임 객체 검출,” 전자공학회 논문지, 제 47권
    또안 박순영 박종현 이귀상 조완현 CI 편, 1호, pp. 22-29, Nov [2010]
  • “Mobile Object Tracking Algorithm Using Particle Filter”
    Se Jin Kim Young Hoon Joo 한국지능시스템학회 논문지, vol. 19, no. 4, pp. 586-591 [2009]
  • Zhiyuan Xu and Xiaoming Liu, “Bilinear Interpolation Dynamic Histogram Equalization for Fog-degraded Image Enhancement”, Journal of Information & Computational Science 7: 8, pp. 1727-1732, 2010.
  • Yoav Y. Schechner, Srinivasa G. Narasimhan, Shree K. Nayar, “Polarization-based vision through haze”, APPLIED OPTICS, 42, pp. 511-525, 2003.
  • Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Instant dehazing of images using polarization,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 325-32, 2001.
  • Y. Boykov, O. Veksler, and R. Zabih, “Fast approximate energy minimization via graph cuts”, IEEE TPAMI, 23(11), , 2001, pp.1222-1239.
  • Xiaoqing Liu, O. Veksler, J Samarabandu, “Graph cut with ordering constraints on labels and its applications”, CVPR 2008, June 2008, pp. 23-28.
  • T. Kailath, “The divergence and Bhattacharyya distance measures in signal detection,” IEEE Trans. Commun. Technol.., vol. COM-15, no. 1, pp. 52-60, Feb. 1967.
  • T. Ahonen, A. Hadid, and M. Pietikinen, "Face description with local binary patterns: Application to face recognition," PAMI 2006.
  • Sen-Ching S. Cheung, Chandrika Kamath, “Robust techniques for background subtraction in urban traffic video”, proc. SPIE 5308, Visual Communications and Image processing, pp. 881-892, Jan, 2004.
  • Sen-Ching S. Cheung and Chandrika Kamath : “Robust techniques for background subtraction in urban traffic video”, Proc. SPIE 5308, Visual Communications and Image Processing 2004, pp. 881-892, Jan, 2004.
  • S. Paris and F. Durand, “A fast approximation of the bilateral filter using a signal processing approach,” Int’l J. of Computer Vision, vol. 81, no. 1, pp. 24-52, 2009.
  • S. Osher, M. Burger, D. Goldfarb, J. Xu, and W. Yin, “An iterative regularization method for total variation-based image restoration”, SIAM Journal on Multiscale Modeling and Simulation, vol. 4, no. 2, pp. 460-489, 2005.
  • S. Liao, X. Zhu, Z. Lei, L. Zhang and S. Z. Li, "Learning Multi-scale Block Local Binary Patterns for Face Recognition," ICB 2007.
  • S. Kim, J. Park and S. Park : “Estimation of the Medium Transmission Using Graph-based Image Segmentation and Visibility Restoration”, Journal of The Institute of Electronics Engineering of Korea, Vol. 50, No, 4, pp.923-930, Aprill, 2013
  • S. K. Nayar and S. G. Narasimhan, “Vision in bad weather”, ICCV, pp. 820, 1999.
  • S. G. Narasimhan, S. K. Nayar, “Vision and the Atmosphere”, International Journal of Computer Vision, 48, pp. 233-254, 2002.
  • S. Fang, J. Zhan, Y. Cao, and R. Rao, “Improved Single Image Dehazing Using Segmentation”, Proce. Of 2010 17th ICIP, Set. 26-29 2010, pp. 3589-3592.
  • Ramin Zabih and John Woodfill, "Non-parametric Local Transforms for Computing Visual Correspondence," ECCV 1994.
  • R. Tan, “Visibility in bad weather from a single image,” in Proc. CVPR, pp. 1-8, June 2008.
  • R. Fattal, “Single image dehazing,” ACM Trans. Graphics, vol. 27, no. 3, pp. 1-9, Aug. 2008.
  • R. Cucchiara, M. Piccardi, and A. Prati, “Detecting moving objects, ghosts, and shadows in video streams,” IEEE Transactions on Pattern Analysis and Machine Intelligence 25, pp. 1337-1342, Oct. 2003.
  • Q. Zhou and J. Aggarwal, “Tracking and Classifying moving objects from videos,” in Proceedings of IEEE Workshop on Performance Evaluation of Tracking and Survillance, 2001.
  • Q. Zhang, H. Inaba, and S. Kamata, “Adaptive histogram analysis for image enhancement”, Pacific-Rim Symp. on Image and Video Technology (PSIVT), pp. 408-413, 2010.
  • P. Wayne Power, Johann A. Schoonees, “Understanding Background Mixture Models for Foreground Segmentation”, Proceedings Image and Vision Computing New Zealand, 2002.
  • P. Viola and M. J. Jones, "Rapid Object Detection using a Boosted Cascade of Simple Features," CVPR 2001.
  • P. Remagnino et al, “An integrated traffic and Pedestrian model-based system,” in proceedings of the Eighth British Machine Vision Conference, pp. 380-389, 1997.
  • P. KaewTrakulPong, R. Bowden, “A real time adaptive visual surveillance system for tracking low-resolution colour targets in dynamically changing scenes”, Image and Vision Computing 21, pp. 913-929, 2003.
  • P. KaewTraKulPong, R. Bowden, “An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection”, In Proc. 2nd European Workshop on Advanced Video Based Surveillance System, AVBS01, VIDEO BASED SURVEILLANCE SYSTEMS : Computer Vision and Distributed Processing. September, 2001.
  • P. Chavez, “An improved dark-object substraction technique for atmospheric scattering correction of multispectral data”, Remote Sensing of Environment, 24, pp. 450-479, 1988.
  • P. Carr and R. Hartley, “Improved Single Image Dehazing using Geometry”, In Proc. IEEE DICTA, 2009, pp. 103?110.
  • Ojala, T., Pietikainen, M. and Harwood, D., A Comparative Study of Texture Measures with Classification Based on Feature Distributions. Pattern Recognition 29(1):51-59, 1996.
  • N. Hautiere, J. P. Tarel, D. Aubert, and E. Dumont. “Blind contrast enhancement assessment by gradient ratioing at visible edges,” Image Analysis & Stereology Journal, 27(2):87-95, June 2008.
  • N. Friedman and S. Russell, “Image Segmentation in Video Sequences : A Probalilistic approach,” in proceedings of the Thirteenth Annual Conference on Uncertainty in Artificial Intelligence(UAI-97), pp. 175-181, Morgan Kaufmann Publishers, Inc., (San Francisco, CA), 1997.
  • N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," CVPR 2005.
  • Middleton, W.E.K., “Vision through the Atmosphere,” University of Toronto Press, Toronto, 1952.
  • Massimo Piccardi, “Background subtraction techniques: a review”, IEEE International Conference on Systems, Man and Cybernetics“, pp. 3099-3104, 2004.
  • M. Ozuysal, M. Calonder, V. Lepetit, P. Fua, "Fast Keypoint Recognition using Random Ferns", PAMI 2010.
  • M. Abdullarh-Al-Wadud, Md. Hasanul Kabir, M. Ali Akber Dewan, etc., “A Dynamic Histogram Equalization for Image Contrast Enhancement”, IEEE Transactions on Consumer Electronics, 53, pp. 593-600, 2007.
  • Lowe, D. G., “Distinctive Image Features from Scale-Invariant Keypoints”, IJCV 2004.
  • L. Rudin, S. Osher, and E. Fatemi, “Nonlinear total variation based noise removal algorithms”, Physica D., vol. 60, pp. 259-268, 1992.
  • Kopf, J., B., Chen, B., Cohen, M., Cohen-Or, D., Deussen, O., Uyttendaele, M., and Lischinski, D., “Deep photo:model-based photograph enhancement and viewing,” ACM Transactions on Graphics, 27(5):116:1-116:10, 2008.
  • K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” in Proc. CVPR, June 2009.
  • J. Yumel, J. Renno, D. Greenhill, J. Orwell, and G.A. Jones, “Adaptive Eigen-backgrounds for object detection”, International Conferrence on Image Processing, 2004.
  • J. P. Tarel and N. Hautiere, “Fast visibility restoration from a single color or gray level image,” in Proceedings of IEEE International Conference on Computer Vision(ICCV ‘09), pp. 2201-2208, Kyoto, Japan, 2009.
  • Hu Haibo, Zhao Hong, “Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model”, World Academy of Science, Engineering and Technology 43, 2010.
  • H. Koschmieder, “Theorie der horizontalen sichtweite”, Beitn Phys. Freien Atm., 12:171-181, 1924. 1, 2
  • F. Felzenszwalb, D. P. Huttenlocher, “Efficient graph based image segmentation,” Int’l J. of Computer Vision, vol. 59, pp. 167-181, 2004.
  • F. Durand and J. Dorsey, “Fast bilateral filtering for the display of high dynamic-range images”, ACM Transactions on Graphics (SIGGRAPH 2002), pp. 257-266, 2002.
  • D. Comaniciu, V. Ramesh, and P. Meer, “Real Time Tracking of Non-Rigid Objects Using Mean Shift”, IEEE International Conference Computer Vision and Pattern Recognition, vol. 2, pp. 142-149, 2000.
  • C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” in Proc. ICCV, pp. 839-846, Bombay, India, Jan. 1998.
  • C. Stauffer and W.E.L. Grimson, “Learning Patterns of Activity Using Real-Time Tracking,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, pp. 747-757.
  • C. Stauffer and W.E.L. Grimson, “Adaptive Background Mixture Models for Real-time tracking,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1999.
  • C. R Wren, A. Azarbayejani, T. Darrll, and A. P. Pentland, “Pfinder: real-time tracking of the human body”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 780-758, 1997.
  • Bernhard Froba and Andreas Ernst, “Face Detection with the Modified Census Transform”, FG 2004.
  • A. Levin, D. Lischinski, Y. Weiss, “A closed form solution to natural image matting,” IEEE Trans. Pattern Anal. Mach, Intell., vol. 30, no. 2, pp. 228-242, Feb. 2008.
  • A. K. Tripathi, and S. Mukhopadhyay, “Removal of Fog from Images : A Review”, IETE Technical Review, vol. 29, ISSUE 2, pp. 148-156, MAR-APR, 2012.
  • A. K. Tripathi and S. Mukhopadhyay : “Single image fog removal using anisotropic diffusion”, IET Image Processing, Vol. 6, No. 7, pp. 966-975, 2012
  • ?[1] S. G. Narasimhan, and S. K. Nayar, “Chromatic Framework for Vision in Bad Weather,” IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 598-605, 2000.