메뉴 건너뛰기




Volumn , Issue , 2013, Pages 2571-2578

Representing videos using mid-level discriminative patches

Author keywords

Action Recognition; Video Understanding

Indexed keywords

ACTION CLASSIFICATIONS; ACTION RECOGNITION; HUMAN ACTIONS; SEMANTIC OBJECTS; SPATIO-TEMPORAL PATCHES; STATE-OF-THE-ART PERFORMANCE; TRANSFER TECHNIQUE; VIDEO UNDERSTANDING;

EID: 84887337772     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.332     Document Type: Conference Paper
Times cited : (129)

References (34)
  • 1
    • 0035279879 scopus 로고    scopus 로고
    • The recognition of human movement using temporal templates
    • 2
    • A. Bobick and J. Davis. The recognition of human movement using temporal templates. PAMI, 2001. 2
    • (2001) PAMI
    • Bobick, A.1    Davis, J.2
  • 2
    • 85112851150 scopus 로고    scopus 로고
    • Poselets: Body part detectors trained using 3d human pose annotations
    • 1, 2
    • L. Bourdev and J. Malik. Poselets:body part detectors trained using 3d human pose annotations. In ICCV, 2009. 1, 2
    • (2009) ICCV
    • Bourdev, L.1    Malik, J.2
  • 3
    • 84856661125 scopus 로고    scopus 로고
    • Learning spatiotemporal graphs of human activities
    • 6, 7
    • W. Brendel and S. Todorovic. Learning spatiotemporal graphs of human activities. In ICCV, 2011. 6, 7
    • (2011) ICCV
    • Brendel, W.1    Todorovic, S.2
  • 4
    • 85162332438 scopus 로고    scopus 로고
    • Learning person-object interactions for action recognition in still images
    • 1
    • V. Delaitre, J. Sivic, and I. Laptev. Learning person-object interactions for action recognition in still images. In NIPS, 2011. 1
    • (2011) NIPS
    • Delaitre, V.1    Sivic, J.2    Laptev, I.3
  • 8
    • 84898405815 scopus 로고    scopus 로고
    • Recognizing activities with cluster-trees of tracklets
    • 7
    • A. Gaidon, Z. Harchaoui, and C. Schmid. Recognizing activities with cluster-trees of tracklets. In BMVC, 2012. 7
    • (2012) BMVC
    • Gaidon, A.1    Harchaoui, Z.2    Schmid, C.3
  • 10
    • 69549121743 scopus 로고    scopus 로고
    • Observing humanobject interactions: Using spatial and functional compatibility for recognition
    • 1, 2
    • A. Gupta, A. Kembhavi, and L. S. Davis. Observing humanobject interactions: Using spatial and functional compatibility for recognition. PAMI, 2009. 1, 2
    • (2009) PAMI
    • Gupta, A.1    Kembhavi, A.2    Davis, L.S.3
  • 11
    • 70450202741 scopus 로고    scopus 로고
    • Understanding videos, constructing plots: Learning a visually grounded storyline model from annotated videos
    • 1
    • A. Gupta, P. Srinivasan, J. Shi, and L. S. Davis. Understanding videos, constructing plots: Learning a visually grounded storyline model from annotated videos. In CVPR, 2009. 1
    • (2009) CVPR
    • Gupta, A.1    Srinivasan, P.2    Shi, J.3    Davis, L.S.4
  • 12
    • 50649103739 scopus 로고    scopus 로고
    • Event detection in crowded videos
    • 2
    • Y. Ke, R. Sukthankar, and M. Hebert. Event detection in crowded videos. In ICCV, 2007. 2
    • (2007) ICCV
    • Ke, Y.1    Sukthankar, R.2    Hebert, M.3
  • 13
    • 84898426452 scopus 로고    scopus 로고
    • A spatio-temporal descriptor based on 3d-gradients
    • 3
    • A. Kläser, M. Marsza?ek, and C. Schmid. A spatio-temporal descriptor based on 3d-gradients. In BMVC, 2008. 3
    • (2008) BMVC
    • Kläser, A.1    Marszaek, M.2    Schmid, C.3
  • 14
    • 84880311243 scopus 로고    scopus 로고
    • Learning human activities and object affordances from rgb-d videos
    • 2
    • H. Koppula, R. Gupta, and A. Saxena. Learning human activities and object affordances from rgb-d videos. IJRR, 2013. 2
    • (2013) IJRR
    • Koppula, H.1    Gupta, R.2    Saxena, A.3
  • 15
    • 77955993558 scopus 로고    scopus 로고
    • Learning a hierarchy of discriminative space-time neighborhood features for human action recognition
    • 2
    • A. Kovashka and K. Grauman. Learning a hierarchy of discriminative space-time neighborhood features for human action recognition. In CVPR, 2010. 2
    • (2010) CVPR
    • Kovashka, A.1    Grauman, K.2
  • 16
    • 84863083227 scopus 로고    scopus 로고
    • Discriminative figure-centric models for joint action localization and recognition
    • 2
    • T. Lan, Y. Wang, and G. Mori. Discriminative figure-centric models for joint action localization and recognition. In ICCV, 2011. 2
    • (2011) ICCV
    • Lan, T.1    Wang, Y.2    Mori, G.3
  • 17
    • 24944451092 scopus 로고    scopus 로고
    • On space-time interest points
    • 2
    • I. Laptev. On space-time interest points. IJCV, 2005. 2
    • (2005) IJCV
    • Laptev, I.1
  • 19
    • 84858731529 scopus 로고    scopus 로고
    • An integer projected fixed point method for graph matching and map inference
    • 5
    • M. Leordeanu, M. Hebert, and R. Sukthankar. An integer projected fixed point method for graph matching and map inference. In NIPS, 2009. 5
    • (2009) NIPS
    • Leordeanu, M.1    Hebert, M.2    Sukthankar, R.3
  • 20
    • 85162513516 scopus 로고    scopus 로고
    • Object bank: A high-level image representation for scene lassification and semantic feature sparsification
    • 4
    • L.-J. Li, H. Su, E. P. Xing, and L. Fei-Fei. Object bank: A high-level image representation for scene lassification and semantic feature sparsification. In NIPS, 2010. 4
    • (2010) NIPS
    • Li, L.-J.1    Su, H.2    Xing, E.P.3    Fei-Fei, L.4
  • 21
    • 70450203660 scopus 로고    scopus 로고
    • Recognizing realistic actions from videos in the wild
    • 2
    • J. Liu, J. Luo, and M. Shah. Recognizing realistic actions from videos in the wild. In CVPR, 2009. 2
    • (2009) CVPR
    • Liu, J.1    Luo, J.2    Shah, M.3
  • 22
    • 84863411575 scopus 로고    scopus 로고
    • Ensemble of exemplar-svms for object detection and beyond
    • 1, 3
    • T. Malisiewicz, A. Gupta, and A. A. Efros. Ensemble of exemplar-svms for object detection and beyond. In ICCV, 2011. 1, 3
    • (2011) ICCV
    • Malisiewicz, T.1    Gupta, A.2    Efros, A.A.3
  • 23
    • 80052874353 scopus 로고    scopus 로고
    • Modeling temporal structure of decomposable motion segments for activity classification
    • 1, 2, 6, 7
    • J. Niebles, C. Chen, and L. Fei-Fei. Modeling temporal structure of decomposable motion segments for activity classification. In ECCV, 2010. 1, 2, 6, 7
    • (2010) ECCV
    • Niebles, J.1    Chen, C.2    Fei-Fei, L.3
  • 24
    • 45049084813 scopus 로고    scopus 로고
    • Unsupervised learning of human action categories using spatial-temporal words
    • 2, 5
    • J. C. Niebles, H. Wang, and L. Fei-Fei. Unsupervised learning of human action categories using spatial-temporal words. IJCV, 2008. 2, 5
    • (2008) IJCV
    • Niebles, J.C.1    Wang, H.2    Fei-Fei, L.3
  • 25
    • 84866661728 scopus 로고    scopus 로고
    • Discovering discriminative action parts from mid-level video representations
    • 2
    • M. Raptis, I. Kokkinos, and S. Soatto. Discovering discriminative action parts from mid-level video representations. In CVPR, 2012. 2
    • (2012) CVPR
    • Raptis, M.1    Kokkinos, I.2    Soatto, S.3
  • 26
    • 84866718894 scopus 로고    scopus 로고
    • Action bank: A high-level representation of activity in video
    • 2, 6
    • S. Sadanand and J. J. Corso. Action bank: A high-level representation of activity in video. In CVPR, 2012. 2, 6
    • (2012) CVPR
    • Sadanand, S.1    Corso, J.J.2
  • 27
    • 80052901415 scopus 로고    scopus 로고
    • Modeling the temporal extent of actions
    • 1
    • S. Satkin and M. Hebert. Modeling the temporal extent of actions. In ECCV, 2010. 1
    • (2010) ECCV
    • Satkin, S.1    Hebert, M.2
  • 28
    • 37849037402 scopus 로고    scopus 로고
    • A 3-dimensional sift descriptor and its application to action recognition
    • 2
    • P. Scovanner, S. Ali, and M. Shah. A 3-dimensional sift descriptor and its application to action recognition. In ACM Multimedia, 2007. 2
    • (2007) ACM Multimedia
    • Scovanner, P.1    Ali, S.2    Shah, M.3
  • 29
    • 84887325615 scopus 로고    scopus 로고
    • Similarity constrained latent support vector machine: An application to weakly supervised action classification
    • 2
    • N. Shapovalova, A. Vahdat, K. Cannons, T. Lan, and G. Mori. Similarity constrained latent support vector machine: An application to weakly supervised action classification. In ECCV, 2012. 2
    • (2012) ECCV
    • Shapovalova, N.1    Vahdat, A.2    Cannons, K.3    Lan, T.4    Mori, G.5
  • 30
    • 84856636962 scopus 로고    scopus 로고
    • Unsupervised learning of event and-or grammar and semantics from video
    • Z. Si, M. Pei, and S. Zhu. Unsupervised learning of event and-or grammar and semantics from video. In ICCV, 2011.
    • (2011) ICCV
    • Si, Z.1    Pei, M.2    Zhu, S.3
  • 31
    • 84884958786 scopus 로고    scopus 로고
    • Unsupervised discovery of mid-level discriminative patches
    • 1, 2
    • S. Singh, A. Gupta, and A. A. Efros. Unsupervised discovery of mid-level discriminative patches. In ECCV, 2012. 1, 2
    • (2012) ECCV
    • Singh, S.1    Gupta, A.2    Efros, A.A.3
  • 32
    • 84898890371 scopus 로고    scopus 로고
    • Evaluation of local spatio-temporal features for action recognition
    • 2
    • H. Wang, M. M. Ullah, A. Klaser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. In BMVC, 2009. 2
    • (2009) BMVC
    • Wang, H.1    Ullah, M.M.2    Klaser, A.3    Laptev, I.4    Schmid, C.5
  • 33
    • 79957467077 scopus 로고    scopus 로고
    • Hidden part models for human action recognition: Probabilistic versus max margin
    • 2
    • Y. Wang and G. Mori. Hidden part models for human action recognition:probabilistic versus max margin. PAMI, 2011. 2
    • (2011) PAMI
    • Wang, Y.1    Mori, G.2
  • 34
    • 84856672971 scopus 로고    scopus 로고
    • Action recognition by learning bases of action attributes and parts
    • 2
    • B. Yao, X. Jiang, A. Khosla, A. L. Lin, L. J. Guibas, and L. Fei-Fei. Action recognition by learning bases of action attributes and parts. In ICCV, 2011. 2
    • (2011) ICCV
    • Yao, B.1    Jiang, X.2    Khosla, A.3    Lin, A.L.4    Guibas, L.J.5    Fei-Fei, L.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.