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2015 | OriginalPaper | Chapter

Human-Object Interaction Recognition by Modeling Context

Authors : Qun Zhang, Wei Liang, Xiabing Liu, Yumeng Wang

Published in: Image and Graphics

Publisher: Springer International Publishing

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Abstract

In this paper, we present a new method to recognize human-object interactions by modeling the context between human actions and manipulated objects. It is a challenging task due to severe occlusion between human and objects during the interacting process. While human actions and objects can provide strong context information, such as some action happening is usually related to a certain object, by which we can improve the accuracy of recognition for both of them. In this paper, we use global and local temporal features from skeleton sequences to model actions, and kernel features are applied to describe objects. We optimize all possible solutions from actions and objects by modeling the context between them. The results of experiments show the effectiveness of our method.

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Bo, L., Ren, X., Fox, D.: Kernel descriptors for visual recognition. In: Advances in Neural Information Processing Systems, pp. 244–252 (2010)

Bo, L., Ren, X., Fox, D.: Depth kernel descriptors for object recognition. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 821–826. IEEE (2011)

Bo, L., Sminchisescu, C.: Efficient match kernel between sets of features for visual recognition. In: Advances in Neural Information Processing Systems, pp. 135–143 (2009)

Bobick, A.F., Davis, J.W.: The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal. Mach. Intell. 23(3), 257–267 (2001)CrossRef

Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 27 (2011)

Chen, D.Y., Shih, S.W., Liao, H.Y.: Human action recognition using 2-d spatio-temporal templates. In: 2007 IEEE International Conference on Multimedia and Expo, pp. 667–670. IEEE (2007)

Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886–893. IEEE (2005)

Flitton, G.T., Breckon, T.P., Bouallagu, N.M.: Object recognition using 3d sift in complex CT volumes. In: BMVC, pp. 1–12 (2010)

Grauman, K., Darrell, T.: The pyramid match kernel: discriminative classification with sets of image features. In: 2005 Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 2, pp. 1458–1465. IEEE (2005)

10.

Gupta, A., Kembhavi, A., Davis, L.S.: Observing human-object interactions: using spatial and functional compatibility for recognition. IEEE Trans. Pattern Anal. Mach. Intell. 31(10), 1775–1789 (2009)CrossRef

11.

Ito, S., Kubota, S.: Object classification using heterogeneous co-occurrence features. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part V. LNCS, vol. 6315, pp. 701–714. Springer, Heidelberg (2010) CrossRef

12.

Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 951–958. IEEE (2009)

13.

Liang, Y., Lu, W., Liang, W., Wang, Y.: Action recognition using local joints structure and histograms of 3d joints. In: 2014 Tenth International Conference on Computational Intelligence and Security (CIS), pp. 185–188. IEEE (2014)

14.

Lin, Z., Jiang, Z., Davis, L.S.: Recognizing actions by shape-motion prototype trees. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 444–451. IEEE (2009)

15.

Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef

16.

Marszalek, M., Laptev, I., Schmid, C.: Actions in context. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 2929–2936. IEEE (2009)

17.

Raptis, M., Soatto, S.: Tracklet descriptors for action modeling and video analysis. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 577–590. Springer, Heidelberg (2010) CrossRef

18.

Su, Y., Allan, M., Jurie, F.: Improving object classification using semantic attributes. In: BMVC, pp. 1–10 (2010)

19.

Sun, J., Wu, X., Yan, S., Cheong, L.F., Chua, T.S., Li, J.: Hierarchical spatio-temporal context modeling for action recognition. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 2004–2011. IEEE (2009)

20.

Wei, P., Zhao, Y., Zheng, N., Zhu, S.C.: Modeling 4d human-object interactions for event and object recognition. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 3272–3279. IEEE (2013)

21.

Xia, L., Chen, C.C., Aggarwal, J.: View invariant human action recognition using histograms of 3d joints. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 20–27. IEEE (2012)

22.

Yao, B., Fei-Fei, L.: Modeling mutual context of object and human pose in human-object interaction activities. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17–24. IEEE (2010)

23.

Yao, B., Fei-Fei, L.: Recognizing human-object interactions in still images by modeling the mutual context of objects and human poses. IEEE Trans. Pattern Anal. Mach. Intell. 34(9), 1691–1703 (2012)CrossRef

24.

Yu, K., Xu, W., Gong, Y.: Deep learning with kernel regularization for visual recognition. In: Advances in Neural Information Processing Systems, pp. 1889–1896 (2009)

25.

Zhang, J., Huang, K., Yu, Y., Tan, T.: Boosted local structured HOG-LBP for object localization. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1393–1400. IEEE (2011)

Title: Human-Object Interaction Recognition by Modeling Context
Authors: Qun Zhang
Wei Liang
Xiabing Liu
Yumeng Wang
Publisher: Springer International Publishing
Book: Image and Graphics
Print ISBN: 978-3-319-21962-2

Electronic ISBN: 978-3-319-21963-9

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-3-319-21963-9_35

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