메뉴 건너뛰기




Volumn , Issue , 2013, Pages 2091-2098

Revisiting depth layers from occlusions

Author keywords

Image based modeling; scene understanding; segmentation

Indexed keywords

IMAGE-BASED MODELING; MARKOV RANDOM FIELDS; MOVING OBJECTS; OBJECT MOTION; SCENE UNDERSTANDING; SMOOTH MOTIONS; SPATIO-TEMPORAL; STATIC CAMERAS;

EID: 84887324741     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.272     Document Type: Conference Paper
Times cited : (8)

References (32)
  • 1
    • 4344598245 scopus 로고    scopus 로고
    • An experimental comparison of mincut/ max-flow algorithms for energy minimization in vision
    • 3
    • Y. Boykov and V. Kolmogorov. An experimental comparison of mincut/ max-flow algorithms for energy minimization in vision. PAMI, 26(9):1124-1137, 2004. 3
    • (2004) PAMI , vol.26 , Issue.9 , pp. 1124-1137
    • Boykov, Y.1    Kolmogorov, V.2
  • 2
    • 0035509961 scopus 로고    scopus 로고
    • Efficient approximate energy minimization via graph cuts
    • 3
    • Y. Boykov, O. Veksler, and R. Zabih. Efficient approximate energy minimization via graph cuts. PAMI, 20(12):1222-1239, 2001. 3
    • (2001) PAMI , vol.20 , Issue.12 , pp. 1222-1239
    • Boykov, Y.1    Veksler, O.2    Zabih, R.3
  • 3
    • 0033283982 scopus 로고    scopus 로고
    • Motion based decompositing of video
    • 1, 2, 3, 4, 6, 7, 8
    • G. Brostow and I. Essa. Motion based decompositing of video. In ICCV, 1999. 1, 2, 3, 4, 6, 7, 8
    • (1999) ICCV
    • Brostow, G.1    Essa, I.2
  • 4
    • 0036565814 scopus 로고    scopus 로고
    • Mean shift: A robust approach toward feature space analysis
    • 2
    • D. Comaniciu and P. Meer. Mean shift: a robust approach toward feature space analysis. PAMI, 24(5):603-619, 2002. 2
    • (2002) PAMI , vol.24 , Issue.5 , pp. 603-619
    • Comaniciu, D.1    Meer, P.2
  • 6
    • 33846606971 scopus 로고    scopus 로고
    • Occlusion analysis: Learning and utilising depthmaps in object tracking
    • 1
    • D. Greenhill, J. Renno, J. Orwell, and G. Jones. Occlusion analysis: Learning and utilising depthmaps in object tracking. In BMVC, 2004. 1
    • (2004) BMVC
    • Greenhill, D.1    Renno, J.2    Orwell, J.3    Jones, G.4
  • 7
    • 84874749114 scopus 로고    scopus 로고
    • Probabilistic multi-view dynamic scene reconstruction and occlusion reasoning from silhouette cues
    • 2, 5
    • L. Guan, J. Franco, and M. Pollefeys. Probabilistic multi-view dynamic scene reconstruction and occlusion reasoning from silhouette cues. In IJCV, 2010. 2, 5
    • (2010) IJCV
    • Guan, L.1    Franco, J.2    Pollefeys, M.3
  • 8
    • 78149319842 scopus 로고    scopus 로고
    • Blocks world revisited: Image understanding using qualitative geometry and mechanics
    • 1, 2
    • A. Gupta, A. Efros, and M. Hebert. Blocks world revisited: Image understanding using qualitative geometry and mechanics. In ECCV, 2010. 1, 2
    • (2010) ECCV
    • Gupta, A.1    Efros, A.2    Hebert, M.3
  • 9
    • 80052872729 scopus 로고    scopus 로고
    • From 3d scene geometry to human workspace
    • 2
    • A. Gupta, S. Satkin, A. Efros, and M. Hebert. From 3d scene geometry to human workspace. In CVPR, 2011. 2
    • (2011) CVPR
    • Gupta, A.1    Satkin, S.2    Efros, A.3    Hebert, M.4
  • 10
    • 77953216235 scopus 로고    scopus 로고
    • Recovering the spatial layout of cluttered rooms
    • 1, 2
    • V. Hedau, D. Hoiem, and D. Forsyth. Recovering the spatial layout of cluttered rooms. In ICCV, 2009. 1, 2
    • (2009) ICCV
    • Hedau, V.1    Hoiem, D.2    Forsyth, D.3
  • 11
    • 80051958131 scopus 로고    scopus 로고
    • Thinking inside the box: Using appearance models and context based on room geometry
    • 2
    • V. Hedau, D. Hoiem, and D. Forsyth. Thinking inside the box: Using appearance models and context based on room geometry. In ECCV, 2010. 2
    • (2010) ECCV
    • Hedau, V.1    Hoiem, D.2    Forsyth, D.3
  • 12
    • 51349086291 scopus 로고    scopus 로고
    • Putting objects in perspective
    • 1, 2
    • D. Hoiem, A. Efros, and M. Hebert. Putting objects in perspective. In IJCV, 2008. 1, 2
    • (2008) IJCV
    • Hoiem, D.1    Efros, A.2    Hebert, M.3
  • 13
    • 79851509434 scopus 로고    scopus 로고
    • Recovering occlusion boundaries from an image
    • 1, 2, 3, 4, 6, 7, 8
    • D. Hoiem, A. Efros, and M. Hebert. Recovering occlusion boundaries from an image. In IJCV, 2011. 1, 2, 3, 4, 6, 7, 8
    • (2011) IJCV
    • Hoiem, D.1    Efros, A.2    Hebert, M.3
  • 14
    • 0030684389 scopus 로고    scopus 로고
    • Tour into the picture: Using a spidery mesh interface to make animation from a single image
    • 2
    • Y. Horry, K. Aniyo, and K. Arai. Tour into the picture: Using a spidery mesh interface to make animation from a single image. In SIGGRAPH, 1997. 2
    • (1997) SIGGRAPH
    • Horry, Y.1    Aniyo, K.2    Arai, K.3
  • 15
    • 24644439301 scopus 로고    scopus 로고
    • Tracking multiple objects through occlusions
    • 1
    • Y. Huang and I. Essa. Tracking multiple objects through occlusions. In CVPR, 2005. 1
    • (2005) CVPR
    • Huang, Y.1    Essa, I.2
  • 16
    • 84866674047 scopus 로고    scopus 로고
    • A learning based framework for depth ordering
    • 2, 4
    • Z. Jia, A. Gallagher, Y. Chang, and T. Chen. A learning based framework for depth ordering. In CVPR, 2012. 2, 4
    • (2012) CVPR
    • Jia, Z.1    Gallagher, A.2    Chang, Y.3    Chen, T.4
  • 17
    • 0004062142 scopus 로고
    • Organization in vision: Essays on gestalt perception
    • 2
    • G. Kanizsa. Organization in vision: Essays on gestalt perception. In Praeger, 1979. 2
    • (1979) Praeger
    • Kanizsa, G.1
  • 18
    • 0002282074 scopus 로고
    • A new measure of rank correlation
    • 6
    • M. Kendall. A new measure of rank correlation. Biometrika, 30:81-93, 1938. 6
    • (1938) Biometrika , vol.30 , pp. 81-93
    • Kendall, M.1
  • 19
    • 33750129298 scopus 로고    scopus 로고
    • Convergent tree-reweighted message passing for energy minimization
    • Oct. 5
    • V. Kolmogorov. Convergent tree-reweighted message passing for energy minimization. PAMI, 28(10):1568-1583, Oct. 2006. 5
    • (2006) PAMI , vol.28 , Issue.10 , pp. 1568-1583
    • Kolmogorov, V.1
  • 20
    • 0742286180 scopus 로고    scopus 로고
    • What energy functions can be minimized via graph cuts?
    • 3
    • V. Kolmogorov and R. Zabih. What energy functions can be minimized via graph cuts? PAMI, 26(2):147-159, 2004. 3
    • (2004) PAMI , vol.26 , Issue.2 , pp. 147-159
    • Kolmogorov, V.1    Zabih, R.2
  • 21
    • 80052905388 scopus 로고    scopus 로고
    • Active learning for piecewise planar 3d reconstruction
    • 4
    • A. Kowdle, Y. Chang, A. Gallagher, and T. Chen. Active learning for piecewise planar 3d reconstruction. In CVPR, 2011. 4
    • (2011) CVPR
    • Kowdle, A.1    Chang, Y.2    Gallagher, A.3    Chen, T.4
  • 22
    • 84867851860 scopus 로고    scopus 로고
    • Bayesian autocalibration for surveillance
    • 1
    • N. Krahnstoever and P. Mendonca. Bayesian autocalibration for surveillance. In CVPR, 2005. 1
    • (2005) CVPR
    • Krahnstoever, N.1    Mendonca, P.2
  • 23
    • 85161973668 scopus 로고    scopus 로고
    • Estimating spatial layout of rooms using volumetric reasoning about objects and surfaces
    • 1, 2
    • D. Lee, A. Gupta, M. Hebert, and T. Kanade. Estimating spatial layout of rooms using volumetric reasoning about objects and surfaces. In NIPS, 2010. 1, 2
    • (2010) NIPS
    • Lee, D.1    Gupta, A.2    Hebert, M.3    Kanade, T.4
  • 25
    • 0021824104 scopus 로고
    • Biological image motion processing
    • 2
    • K. Nakayama. Biological image motion processing. In Vision Research, volume 25, pages 625-660, 1985. 2
    • (1985) Vision Research , vol.25 , pp. 625-660
    • Nakayama, K.1
  • 27
    • 84877632511 scopus 로고    scopus 로고
    • Grabcut"-Interactive foreground extraction using iterated graph cuts
    • 3, 5
    • C. Rother, V. Kolmogorov, and A. Blake. "Grabcut"-Interactive foreground extraction using iterated graph cuts. In SIGGRAPH, 2004. 3, 5
    • (2004) SIGGRAPH
    • Rother, C.1    Kolmogorov, V.2    Blake, A.3
  • 28
    • 77953066727 scopus 로고    scopus 로고
    • Learning depth from single monocular images
    • 1, 2
    • A. Saxena, S. Chung, and A. Ng. Learning depth from single monocular images. In NIPS, 2005. 1, 2
    • (2005) NIPS
    • Saxena, A.1    Chung, S.2    Ng, A.3
  • 29
    • 0035680188 scopus 로고    scopus 로고
    • Depth layers from occlusions
    • 1, 2
    • A. Schodl and I. Essa. Depth layers from occlusions. In CVPR, 2001. 1, 2
    • (2001) CVPR
    • Schodl, A.1    Essa, I.2
  • 30
    • 67649286026 scopus 로고    scopus 로고
    • Depth compositing for augmented reality
    • 1
    • J. Ventura and T. H"ollerer. Depth compositing for augmented reality. In SIGGRAPH, 2008. 1
    • (2008) SIGGRAPH
    • Ventura, J.1    Hollerer, T.2
  • 31
    • 80051967993 scopus 로고    scopus 로고
    • Discriminative learning with latent variables for cluttered indoor scene understanding
    • 1, 2
    • H. Wang, S. Gould, and D. Koller. Discriminative learning with latent variables for cluttered indoor scene understanding. In ECCV, 2010. 1, 2
    • (2010) ECCV
    • Wang, H.1    Gould, S.2    Koller, D.3
  • 32
    • 51849091871 scopus 로고    scopus 로고
    • Inferring spatial layout from a single image via depth-ordered grouping
    • 1, 2
    • S. Yu, H. Zhang, and J. Malik. Inferring spatial layout from a single image via depth-ordered grouping. In POCV Workshop, 2008. 1, 2
    • (2008) POCV Workshop
    • Yu, S.1    Zhang, H.2    Malik, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.