메뉴 건너뛰기




Volumn 9905 LNCS, Issue , 2016, Pages 280-296

Real-time RGB-D activity prediction by soft regression

Author keywords

Activity prediction; RGB D; Soft regression

Indexed keywords

COMPUTER VISION; FORECASTING;

EID: 84990045090     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46448-0_17     Document Type: Conference Paper
Times cited : (79)

References (44)
  • 1
    • 84961588783 scopus 로고    scopus 로고
    • Anticipating human activities using object affordances for reactive robotic response
    • Koppula, H.S., Saxena, A.: Anticipating human activities using object affordances for reactive robotic response. IEEE Trans. Pattern Anal. Mach. Intell. 38(1), 14–29 (2016)
    • (2016) IEEE Trans. Pattern Anal. Mach. Intell , vol.38 , Issue.1 , pp. 14-29
    • Koppula, H.S.1    Saxena, A.2
  • 2
    • 84880311243 scopus 로고    scopus 로고
    • Learning human activities and object affordances from RGB-D videos
    • Koppula, H.S., Gupta, R., Saxena, A.: Learning human activities and object affordances from RGB-D videos. Int. J. Robot. Res. 32(8), 951–970 (2013)
    • (2013) Int. J. Robot. Res , vol.32 , Issue.8 , pp. 951-970
    • Koppula, H.S.1    Gupta, R.2    Saxena, A.3
  • 3
    • 84906490435 scopus 로고    scopus 로고
    • A hierarchical representation for future action prediction
    • Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.), Springer, Heidelberg
    • Lan, T., Chen, T.-C., Savarese, S.: A hierarchical representation for future action prediction. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8691, pp. 689–704. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10578-945
    • (2014) ECCV 2014. LNCS , vol.8691 , pp. 689-704
    • Lan, T.1    Chen, T.-C.2    Savarese, S.3
  • 4
    • 84904183969 scopus 로고    scopus 로고
    • Prediction of human activity by discovering temporal sequence patterns
    • Li, K., Fu, Y.: Prediction of human activity by discovering temporal sequence patterns. IEEE Trans. Pattern Anal. Mach. Intell. 36(8), 1644–1657 (2014)
    • (2014) IEEE Trans. Pattern Anal. Mach. Intell , vol.36 , Issue.8 , pp. 1644-1657
    • Li, K.1    Fu, Y.2
  • 5
    • 84929626784 scopus 로고    scopus 로고
    • Discriminative orderlet mining for real-time recognition of human-object interaction
    • Cremers, D., Reid, I., Saito, H., Yang, M.-H. (eds.), Springer, Heidelberg
    • Yu, G., Liu, Z., Yuan, J.: Discriminative orderlet mining for real-time recognition of human-object interaction. In: Cremers, D., Reid, I., Saito, H., Yang, M.-H. (eds.) ACCV 2014. LNCS, vol. 9007, pp. 50–65. Springer, Heidelberg (2015). doi:10.1007/978-3-319-16814-2_4
    • (2015) ACCV 2014. LNCS , vol.9007 , pp. 50-65
    • Yu, G.1    Liu, Z.2    Yuan, J.3
  • 7
    • 84906492500 scopus 로고    scopus 로고
    • A discriminative model with multiple temporal scales for action prediction
    • Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.), Springer, Heidelberg
    • Kong, Y., Kit, D., Fu, Y.: A discriminative model with multiple temporal scales for action prediction. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 596–611. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10602-1_39
    • (2014) ECCV 2014. LNCS , vol.8693 , pp. 596-611
    • Kong, Y.1    Kit, D.2    Fu, Y.3
  • 8
    • 84856688144 scopus 로고    scopus 로고
    • Human activity prediction: Early recognition of ongoing activities from streaming videos
    • Ryoo, M.: Human activity prediction: Early recognition of ongoing activities from streaming videos. In: International Conference on Computer Vision, pp. 1036–1043 (2011)
    • (2011) International Conference on Computer Vision , pp. 1036-1043
    • Ryoo, M.1
  • 9
    • 84973917927 scopus 로고    scopus 로고
    • Activity auto-completion: Predicting human activities from partial videos
    • Xu, Z., Qing, L., Miao, J.: Activity auto-completion: predicting human activities from partial videos. In: IEEE International Conference on Computer Vision, pp. 3191–3199 (2015)
    • (2015) IEEE International Conference on Computer Vision , pp. 3191-3199
    • Xu, Z.1    Qing, L.2    Miao, J.3
  • 10
  • 12
    • 84897108420 scopus 로고    scopus 로고
    • Max-margin early event detectors
    • Hoai, M., De la Torre, F.: Max-margin early event detectors. Int. J. Comput. Vis. 107(2), 191–202 (2014)
    • (2014) Int. J. Comput. Vis , vol.107 , Issue.2 , pp. 191-202
    • Hoai, M.1    De La Torre, F.2
  • 13
    • 84867863926 scopus 로고    scopus 로고
    • Activity forecasting
    • Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.), Springer, Heidelberg
    • Kitani, K.M., Ziebart, B.D., Bagnell, J.A., Hebert, M.: Activity forecasting. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7575, pp. 201–214. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33765-9_15
    • (2012) ECCV 2012. LNCS , vol.7575 , pp. 201-214
    • Kitani, K.M.1    Ziebart, B.D.2    Bagnell, J.A.3    Hebert, M.4
  • 15
    • 84906489572 scopus 로고    scopus 로고
    • Sequential max-margin event detectors
    • Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.), Springer, Heidelberg
    • Huang, D., Yao, S., Wang, Y., Torre, F.: Sequential max-margin event detectors. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8691, pp. 410–424. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10578-9_27
    • (2014) ECCV 2014. LNCS , vol.8691 , pp. 410-424
    • Huang, D.1    Yao, S.2    Wang, Y.3    Torre, F.4
  • 18
    • 84898426452 scopus 로고    scopus 로고
    • A spatio-temporal descriptor based on 3Dgradients
    • British Machine Vision Association
    • Klaser, A., Marszałek, M., Schmid, C.: A spatio-temporal descriptor based on 3Dgradients. In: British Machine Vision Conference, pp. 275–281. British Machine Vision Association (2008)
    • (2008) British Machine Vision Conference , pp. 275-281
    • Klaser, A.1    Marszałek, M.2    Schmid, C.3
  • 21
    • 84906509652 scopus 로고    scopus 로고
    • Action recognition using super sparse coding vector with spatio-temporal awareness
    • Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.), Springer, Heidelberg
    • Yang, X., Tian, Y.L.: Action recognition using super sparse coding vector with spatio-temporal awareness. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8690, pp. 727–741. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10605-2_47
    • (2014) ECCV 2014. LNCS , vol.8690 , pp. 727-741
    • Yang, X.1    Tian, Y.L.2
  • 29
    • 84867857649 scopus 로고    scopus 로고
    • Robust 3D action recognition with random occupancy patterns
    • Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.), Springer, Heidelberg
    • Wang, J., Liu, Z., Chorowski, J., Chen, Z., Wu, Y.: Robust 3D action recognition with random occupancy patterns. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7573, pp. 872–885. Springer, Heidelberg (2012)
    • (2012) ECCV 2012. LNCS , vol.7573 , pp. 872-885
    • Wang, J.1    Liu, Z.2    Chorowski, J.3    Chen, Z.4    Wu, Y.5
  • 31
    • 84896061825 scopus 로고    scopus 로고
    • Human action recognition using a temporal hierarchy of covariance descriptors on 3D joint locations
    • Hussein, M.E., Torki, M., Gowayyed, M.A., El-Saban, M.: Human action recognition using a temporal hierarchy of covariance descriptors on 3D joint locations. IJCAI 13, 2466–2472 (2013)
    • (2013) IJCAI , vol.13 , pp. 2466-2472
    • Hussein, M.E.1    Torki, M.2    Gowayyed, M.A.3    El-Saban, M.4
  • 35
    • 84891625198 scopus 로고    scopus 로고
    • Sequence of the most informative joints (SMIJ): A new representation for human skeletal action recognition
    • Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., Bajcsy, R.: Sequence of the most informative joints (SMIJ): a new representation for human skeletal action recognition. JVCIR 25(1), 24–38 (2014)
    • (2014) JVCIR , vol.25 , Issue.1 , pp. 24-38
    • Ofli, F.1    Chaudhry, R.2    Kurillo, G.3    Vidal, R.4    Bajcsy, R.5
  • 37
    • 84898773205 scopus 로고    scopus 로고
    • The moving pose: An efficient 3D kinematics descriptor for low-latency action recognition and detection
    • Zanfir, M., Leordeanu, M., Sminchisescu, C.: The moving pose: An efficient 3D kinematics descriptor for low-latency action recognition and detection. In: IEEE International Conference on Computer Vision, pp. 2752–2759 (2013)
    • (2013) IEEE International Conference on Computer Vision , pp. 2752-2759
    • Zanfir, M.1    Leordeanu, M.2    Sminchisescu, C.3
  • 42
    • 84930951838 scopus 로고    scopus 로고
    • Robust structured subspace learning for data representation
    • Li, Z., Liu, J., Tang, J., Lu, H.: Robust structured subspace learning for data representation. IEEE Trans. Pattern Anal. Mach. Intell. 37(10), 2085–2098 (2015)
    • (2015) IEEE Trans. Pattern Anal. Mach. Intell , vol.37 , Issue.10 , pp. 2085-2098
    • Li, Z.1    Liu, J.2    Tang, J.3    Lu, H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.