메뉴 건너뛰기




Volumn , Issue , 2013, Pages 2728-2735

Dynamic pooling for complex event recognition

Author keywords

activity recognition; complex event; pooling; video analysis

Indexed keywords

COMPUTER SCIENCE; ELECTRICAL ENGINEERING;

EID: 84898811014     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.339     Document Type: Conference Paper
Times cited : (42)

References (29)
  • 1
    • 85141266799 scopus 로고    scopus 로고
    • Support vector machines for multiple-instance learning
    • S. Andrews, I. Tsochantaridis, and T. Hofmann. Support vector machines for multiple-instance learning. NIPS, 2002.
    • (2002) NIPS
    • Andrews, S.1    Tsochantaridis, I.2    Hofmann, T.3
  • 3
    • 80052870289 scopus 로고    scopus 로고
    • Probabilistic event logic for interval-based event recognition
    • W. Brendel, A. Fern, and S. Todorovic. Probabilistic event logic for interval-based event recognition. CVPR, 2011.
    • (2011) CVPR
    • Brendel, W.1    Fern, A.2    Todorovic, S.3
  • 4
    • 84856661125 scopus 로고    scopus 로고
    • Learning spatiotemporal graphs of human activities
    • W. Brendel and S. Todorovic. Learning spatiotemporal graphs of human activities. ICCV, 2011.
    • (2011) ICCV
    • Brendel, W.1    Todorovic, S.2
  • 6
    • 50949133669 scopus 로고    scopus 로고
    • Liblinear: A library for large linear classification
    • R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Liblinear: A library for large linear classification. JMLR, 9:1871-1874, 2008.
    • (2008) JMLR , vol.9 , pp. 1871-1874
    • Fan, R.-E.1    Chang, K.-W.2    Hsieh, C.-J.3    Wang, X.-R.4    Lin, C.-J.5
  • 7
    • 77955422240 scopus 로고    scopus 로고
    • Object detection with discriminatively trained part-based models
    • P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part-based models. IEEE TPAMI, 32(9):1627-1645, 2009.
    • (2009) IEEE TPAMI , vol.32 , Issue.9 , pp. 1627-1645
    • Felzenszwalb, P.1    Girshick, R.2    McAllester, D.3    Ramanan, D.4
  • 8
    • 80052915321 scopus 로고    scopus 로고
    • Actom sequence models for efficient action detection
    • A. Gaidon, Z. Harchaoui, and C. Schmid. Actom sequence models for efficient action detection. CVPR, 2011.
    • (2011) CVPR
    • Gaidon, A.1    Harchaoui, Z.2    Schmid, C.3
  • 9
    • 84898405815 scopus 로고    scopus 로고
    • Recognizing activities with cluster-trees of tracklets
    • A. Gaidon, Z. Harchaoui, and C. Schmid. Recognizing activities with cluster-trees of tracklets. BMVC, 2012.
    • (2012) BMVC
    • Gaidon, A.1    Harchaoui, Z.2    Schmid, C.3
  • 10
    • 84866666373 scopus 로고    scopus 로고
    • Beyond spatial pyramids: Receptive field learning for pooled image features
    • Y. Jia, C. Huang, and T. Darrell. Beyond spatial pyramids: Receptive field learning for pooled image features. CVPR, 2012.
    • (2012) CVPR
    • Jia, Y.1    Huang, C.2    Darrell, T.3
  • 11
    • 84877645596 scopus 로고    scopus 로고
    • Trajectorybased modeling of human actions with motion reference points
    • Y.-G. Jiang, Q. Dai, X. Xue, W. Liu, and C.-W. Ngo. Trajectorybased modeling of human actions with motion reference points. ECCV, 2012.
    • (2012) ECCV
    • Jiang, Y.-G.1    Dai, Q.2    Xue, X.3    Liu, W.4    Ngo, C.-W.5
  • 12
    • 0025208765 scopus 로고
    • Proximity control in bundle methods for convex nondifferentiable minimization
    • K. Kiwiel. Proximity control in bundle methods for convex nondifferentiable minimization. Math. Program., 46:105-122, 1990.
    • (1990) Math. Program. , vol.46 , pp. 105-122
    • Kiwiel, K.1
  • 14
    • 84877778010 scopus 로고    scopus 로고
    • Recognizing activities by attribute dynamics
    • W. Li and N. Vasconcelos. Recognizing activities by attribute dynamics. NIPS, 2012.
    • (2012) NIPS
    • Li, W.1    Vasconcelos, N.2
  • 15
    • 84898830888 scopus 로고    scopus 로고
    • Exact linear relaxation of integer linear fractional programming with non-negative denominators
    • W. Li and N. Vasconcelos. Exact linear relaxation of integer linear fractional programming with non-negative denominators. SVCL Technical Report, 2013.
    • (2013) SVCL Technical Report
    • Li, W.1    Vasconcelos, N.2
  • 16
    • 84887384267 scopus 로고    scopus 로고
    • Recognizing activities via bag of words for attribute dynamics
    • W. Li, Q. Yu, H. Sawhney, and N. Vasconcelos. Recognizing activities via bag of words for attribute dynamics. CVPR, 2013.
    • (2013) CVPR
    • Li, W.1    Yu, Q.2    Sawhney, H.3    Vasconcelos, N.4
  • 17
    • 80052874353 scopus 로고    scopus 로고
    • Modeling temporal structure of decomposable motion segments for activity classification
    • J. Niebles, C. Chen, and L. Fei-Fei. Modeling temporal structure of decomposable motion segments for activity classification. ECCV, 2010.
    • (2010) ECCV
    • Niebles, J.1    Chen, C.2    Fei-Fei, L.3
  • 18
    • 50649098663 scopus 로고    scopus 로고
    • Discriminative subsequence mining for action classification
    • S. Nowozin, G. Bakir, and K. Tsuda. Discriminative subsequence mining for action classification. ICCV, 2007.
    • (2007) ICCV
    • Nowozin, S.1    Bakir, G.2    Tsuda, K.3
  • 20
    • 80052901415 scopus 로고    scopus 로고
    • Modeling the temporal extent of actions
    • S. Satkin and M. Hebert. Modeling the temporal extent of actions. ECCV, 2010.
    • (2010) ECCV
    • Satkin, S.1    Hebert, M.2
  • 21
    • 51949101597 scopus 로고    scopus 로고
    • Action snippets: How many frames does human action recognition require?
    • K. Schindler and L. V. Gool. Action snippets: How many frames does human action recognition require? CVPR, 2008.
    • (2008) CVPR
    • Schindler, K.1    Gool, L.V.2
  • 22
    • 84874088405 scopus 로고    scopus 로고
    • A proof of convergence of the concave-convex procedure using zangwill's theory
    • B. K. Sriperumbudur and G. R. G. Lanckriet. A proof of convergence of the concave-convex procedure using zangwill's theory. Neural Computation, 24:1391-1407, 2012.
    • (2012) Neural Computation , vol.24 , pp. 1391-1407
    • Sriperumbudur, B.K.1    Lanckriet, G.R.G.2
  • 23
    • 84866658784 scopus 로고    scopus 로고
    • Learning latent temporal structure for complex event detection
    • K. Tang, L. Fei-Fei, and D. Koller. Learning latent temporal structure for complex event detection. CVPR, 2012.
    • (2012) CVPR
    • Tang, K.1    Fei-Fei, L.2    Koller, D.3
  • 24
    • 84897470376 scopus 로고    scopus 로고
    • Human activities as stochastic kronecker graphs
    • S. Todorovic. Human activities as stochastic kronecker graphs. ECCV, 2012.
    • (2012) ECCV
    • Todorovic, S.1
  • 25
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Large margin methods for structured and interdependent output variables. JMLR, 6:1453-1484, 2005.
    • (2005) JMLR , vol.6 , pp. 1453-1484
    • Tsochantaridis, I.1    Hofmann, T.2    Joachims, T.3    Altun, Y.4
  • 26
    • 84856194352 scopus 로고    scopus 로고
    • Efficient additive kernels via explicit feature maps
    • A. Vedaldi and A. Zisserman. Efficient additive kernels via explicit feature maps. IEEE TPAMI, 34(3):480-492, 2012.
    • (2012) IEEE TPAMI , vol.34 , Issue.3 , pp. 480-492
    • Vedaldi, A.1    Zisserman, A.2
  • 28
    • 84898890371 scopus 로고    scopus 로고
    • Evaluation of local spatio-temporal features for action recognition
    • H. Wang, M. Ullah, A. Kl̈aser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. BMVC, 2009.
    • (2009) BMVC
    • Wang, H.1    Ullah, M.2    Kl̈aser, A.3    Laptev, I.4    Schmid, C.5
  • 29
    • 33747138721 scopus 로고    scopus 로고
    • The concave-convex procedure (cccp)
    • A. L. Yuille and A. Rangarajan. The concave-convex procedure (cccp). NIPS, 2003.
    • (2003) NIPS
    • Yuille, A.L.1    Rangarajan, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.