메뉴 건너뛰기




Volumn 7573 LNCS, Issue PART 2, 2012, Pages 400-413

Structured image segmentation using kernelized features

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; CONDITIONAL RANDOM FIELD; DATA SETS; LINEAR KERNEL; MODEL PARAMETERS; NEURAL TISSUE; OPTIMAL PERFORMANCE; STATE-OF-THE-ART APPROACH; STRUCTURED LEARNING;

EID: 84867856488     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33709-3_29     Document Type: Conference Paper
Times cited : (65)

References (27)
  • 1
    • 14344250451 scopus 로고    scopus 로고
    • Support vector machine learning for interdependent and structured output spaces
    • Tsochantaridis, I., Hofmann, T., Joachims, T., Altun, Y.: Support vector machine learning for interdependent and structured output spaces. In: ICML (2004)
    • (2004) ICML
    • Tsochantaridis, I.1    Hofmann, T.2    Joachims, T.3    Altun, Y.4
  • 2
    • 58149151266 scopus 로고    scopus 로고
    • Textonboost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context
    • Shotton, J.,Winn, J., Rother, C., Criminisi, A.: Textonboost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context. IJCV 81 (2009)
    • (2009) IJCV , vol.81
    • Shotton, J.1    Winn, J.2    Rother, C.3    Criminisi, A.4
  • 3
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • Lafferty, J., McCallum, A., Pereira, F.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: ICML (2001)
    • (2001) ICML
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 5
    • 56749103990 scopus 로고    scopus 로고
    • Learning CRFs Using Graph Cuts
    • Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. Springer, Heidelberg
    • Szummer, M., Kohli, P., Hoiem, D.: Learning CRFs Using Graph Cuts. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 582-595. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5303 , pp. 582-595
    • Szummer, M.1    Kohli, P.2    Hoiem, D.3
  • 6
    • 78149309521 scopus 로고    scopus 로고
    • On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation
    • Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. Springer, Heidelberg
    • Nowozin, S., Gehler, P.V., Lampert, C.H.: On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 98-111. Springer, Heidelberg (2010)
    • (2010) LNCS , vol.6316 , pp. 98-111
    • Nowozin, S.1    Gehler, P.V.2    Lampert, C.H.3
  • 7
    • 84863059942 scopus 로고    scopus 로고
    • Are Spatial and Global Constraints Really Necessary for Segmentation?
    • Lucchi, A., Li, Y., Boix, X., Smith, K., Fua, P.: Are Spatial and Global Constraints Really Necessary for Segmentation? In: ICCV (2011)
    • (2011) ICCV
    • Lucchi, A.1    Li, Y.2    Boix, X.3    Smith, K.4    Fua, P.5
  • 8
    • 65449143358 scopus 로고    scopus 로고
    • Training structural svms with kernels using sampled cuts
    • Yu, C.N.J., Joachims, T.: Training structural svms with kernels using sampled cuts. In: KDD (2008)
    • (2008) KDD
    • Yu, C.N.J.1    Joachims, T.2
  • 9
    • 84867886825 scopus 로고    scopus 로고
    • Fast support vector machines for structural kernels
    • Aliaksei, M., Severyn, A.: Fast support vector machines for structural kernels. In: ECML (2011)
    • (2011) ECML
    • Aliaksei, M.1    Severyn, A.2
  • 10
    • 77953218689 scopus 로고    scopus 로고
    • Random features for large-scale kernel machines
    • Rahimi, A., Recht, B.: Random features for large-scale kernel machines. In: NIPS (2007)
    • (2007) NIPS
    • Rahimi, A.1    Recht, B.2
  • 11
    • 33749033927 scopus 로고    scopus 로고
    • Kernels as features: On kernels, margins, and low-dimensional mappings
    • Balcan, M.F., Blum, A., Vempala, S.: Kernels as features: On kernels, margins, and low-dimensional mappings. Mach. Learn. 65, 79-94 (2006)
    • (2006) Mach. Learn. , vol.65 , pp. 79-94
    • Balcan, M.F.1    Blum, A.2    Vempala, S.3
  • 12
    • 84866662628 scopus 로고    scopus 로고
    • Efficient additive kernels via explicit feature maps
    • Vedaldi, A., Zisserman, A.: Efficient additive kernels via explicit feature maps. In: PAMI (2011)
    • (2011) PAMI
    • Vedaldi, A.1    Zisserman, A.2
  • 13
    • 77953184603 scopus 로고    scopus 로고
    • Max-Margin Additive Classifiers for Detection
    • Maji, S., Berg, A.: Max-Margin Additive Classifiers for Detection. In: ICCV (2009)
    • (2009) ICCV
    • Maji, S.1    Berg, A.2
  • 14
    • 80053436893 scopus 로고    scopus 로고
    • Locally Linear Support Vector Machines
    • Ladicky, L., Torr, P.: Locally Linear Support Vector Machines. In: ICML (2011)
    • (2011) ICML
    • Ladicky, L.1    Torr, P.2
  • 15
    • 80052894155 scopus 로고    scopus 로고
    • Kernelized Structural Svm Learning for Supervised Object Segmentation
    • Bertelli, L., Yu, T., Vu, D., Gokturk, B.: Kernelized Structural Svm Learning for Supervised Object Segmentation. In: CVPR (2011)
    • (2011) CVPR
    • Bertelli, L.1    Yu, T.2    Vu, D.3    Gokturk, B.4
  • 16
    • 84866657764 scopus 로고    scopus 로고
    • SLIC Superpixels Compared to State-of-the-art Superpixel Methods
    • in press, 2012
    • Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Suesstrunk, S.: SLIC Superpixels Compared to State-of-the-art Superpixel Methods. PAMI (in press, 2012)
    • PAMI
    • Achanta, R.1    Shaji, A.2    Smith, K.3    Lucchi, A.4    Fua, P.5    Suesstrunk, S.6
  • 17
    • 0035509961 scopus 로고    scopus 로고
    • Fast Approximate Energy Minimization via Graph Cuts
    • Boykov, Y., Veksler, O., Zabih, R.: Fast Approximate Energy Minimization via Graph Cuts. PAMI 23 (2001)
    • (2001) PAMI , vol.23
    • Boykov, Y.1    Veksler, O.2    Zabih, R.3
  • 18
    • 84899009025 scopus 로고    scopus 로고
    • Bayesian Map Learning in Dynamic Environments
    • Murphy, K.: Bayesian Map Learning in Dynamic Environments. In: NIPS, pp. 1015-1021 (1999)
    • (1999) NIPS , pp. 1015-1021
    • Murphy, K.1
  • 19
    • 0742286180 scopus 로고    scopus 로고
    • What Energy Functions Can Be Minimized via Graph Cuts?
    • Kolmogorov, V., Zabih, R.: What Energy Functions Can Be Minimized via Graph Cuts? PAMI 26, 147-159 (2004)
    • (2004) PAMI , vol.26 , pp. 147-159
    • Kolmogorov, V.1    Zabih, R.2
  • 20
    • 56449113929 scopus 로고    scopus 로고
    • Training structural SVMs when exact inference is intractable
    • Finley, T., Joachims, T.: Training structural SVMs when exact inference is intractable. In: ICML (2008)
    • (2008) ICML
    • Finley, T.1    Joachims, T.2
  • 21
    • 77955998994 scopus 로고    scopus 로고
    • Harmony Potentials for Joint Classification and Segmentation
    • Gonfaus, J., Boix, X., Weijer, J., Bagdanov, A., Serrat, J., Gonzalez, J.: Harmony Potentials for Joint Classification and Segmentation. In: CVPR, pp. 3280-3287 (2010)
    • (2010) CVPR , pp. 3280-3287
    • Gonfaus, J.1    Boix, X.2    Weijer, J.3    Bagdanov, A.4    Serrat, J.5    Gonzalez, J.6
  • 22
    • 56749102464 scopus 로고    scopus 로고
    • Kernel Codebooks for Scene Categorization
    • Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. Springer, Heidelberg
    • van Gemert, J.C., Geusebroek, J.-M., Veenman, C.J., Smeulders, A.W.M.: Kernel Codebooks for Scene Categorization. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 696-709. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5304 , pp. 696-709
    • Van Gemert, J.C.1    Geusebroek, J.-M.2    Veenman, C.J.3    Smeulders, A.W.M.4
  • 23
    • 51949114829 scopus 로고    scopus 로고
    • Semantic Texton Forests for Image Categorization and Segmentation
    • Shotton, J., Johnson, M., Cipolla, P.: Semantic Texton Forests for Image Categorization and Segmentation. In: CVPR (2008)
    • (2008) CVPR
    • Shotton, J.1    Johnson, M.2    Cipolla, P.3
  • 24
    • 77953225585 scopus 로고    scopus 로고
    • Associative Hierarchical CRFs for Object Class Image Segmentation
    • Ladicky, L., Russell, C., Kohli, P., Torr, P.H.S.: Associative Hierarchical CRFs for Object Class Image Segmentation. In: ICCV (2009)
    • (2009) ICCV
    • Ladicky, L.1    Russell, C.2    Kohli, P.3    Torr, P.H.S.4
  • 25
    • 84856735789 scopus 로고    scopus 로고
    • Supervoxel-Based Segmentation of Mitochondria in Em Image Stacks with Learned Shape Features
    • Lucchi, A., Smith, K., Achanta, R., Knott, G., Fua, P.: Supervoxel-Based Segmentation of Mitochondria in Em Image Stacks with Learned Shape Features. TMI 31, 474-486 (2011)
    • (2011) TMI , vol.31 , pp. 474-486
    • Lucchi, A.1    Smith, K.2    Achanta, R.3    Knott, G.4    Fua, P.5
  • 26
    • 51949101231 scopus 로고    scopus 로고
    • A Discriminatively Trained, Multiscale, Deformable Part Model
    • Felzenszwalb, P., Mcallester, D., Ramanan, D.: A Discriminatively Trained, Multiscale, Deformable Part Model. In: CVPR (2008)
    • (2008) CVPR
    • Felzenszwalb, P.1    Mcallester, D.2    Ramanan, D.3
  • 27
    • 77953218049 scopus 로고    scopus 로고
    • Fast Ray Features for Learning Irregular Shapes
    • Smith, K., Carleton, A., Lepetit, V.: Fast Ray Features for Learning Irregular Shapes. In: ICCV, pp. 397-404 (2009)
    • (2009) ICCV , pp. 397-404
    • Smith, K.1    Carleton, A.2    Lepetit, V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.