Abstract
In this paper, an interactive system for human action video search is developed based on the dynamic shape volumes. The user is allowed to create a search query by freely and continuously posing any number of actions in front of the Kinect sensor. For the captured query video sequence and each data stream of the human action video database, we extracted useful shape properties on the basis of space-time volumes by exploiting the solution to the Poisson equation. Different from conventional learning-based human action recognition techniques, we apply approximate string matching (ASM) to achieve local alignment for the matching of two video sequences. The experiments demonstrate the effectiveness of our system in support of the user’s search task.
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References
Brunelli, R., Mich, O.: Image retrieval by examples. IEEE Transactions on Multimedia 2(3), 164–171 (2000)
Cao, Y., Wang, H., Wang, C., Li, Z., Zhang, L., Zhang, L.: Mindfinder: interactive sketch-based image search on millions of images. In: Proceedings of the International Conference on Multimedia, MM 2010, pp. 1605–1608. ACM, New York (2010)
Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-time human pose recognition in parts from single depth images. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1297–1304 (2011)
Gorelick, L., Blank, M., Shechtman, E., Irani, M., Basri, R.: Actions as space-time shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(12), 2247–2253 (2007), http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html
Robertson, N., Reid, I.: A general method for human activity recognition in video. Comput. Vis. Image Underst. 104, 232–248 (2006)
Gorelick, L., Galun, M., Sharon, E., Basri, R., Brandt, A.: Shape representation and classification using the poisson equation. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(12), 1991–2005 (2006)
Ren, W., Singh, S., Singh, M., Zhu, Y.: State-of-the-art on spatio-temporal information-based video retrieval. Pattern Recognition 42(2), 267–282 (2009) !ce:title¿ Learning Semantics from Multimedia Content !/ce:title¿
Poppe, R.: A survey on vision-based human action recognition. Image Vision Comput. 28, 976–990 (2010)
Laptev, I., Lindeberg, T.: Space-time interest points. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, vol. 1, pp. 432–439 (2003)
Yilmaz, A., Shah, M.: Actions sketch: a novel action representation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 984–989 (2005)
Dyana, A., Das, S.: Mst-css (multi-spectro-temporal curvature scale space), a novel spatio-temporal representation for content-based video retrieval. IEEE Transactions on Circuits and Systems for Video Technology 20(8), 1080–1094 (2010)
Yeh, M.C., Cheng, K.T.: Fast visual retrieval using accelerated sequence matching. IEEE Transactions on Multimedia 13(2), 320–329 (2011)
OpenNI organization: OpenNI User Guide (2010) (last viewed January 19, 2011) 11:32
PrimeSense Inc.: Prime Sensor NITE 1.3 Algorithms notes. (2010) (last viewed January 19, 2011) 15:34
Bradski, G.: The OpenCV Library (2000) (last viewed January 19, 2011) 11:32
Rodriguez, M., Ahmed, J., Shah, M.: Action mach a spatio-temporal maximum average correlation height filter for action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8 (2008)
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Chen, HM., Cheng, WH., Hu, MC., Lin, YC., Hsieh, YH. (2013). Human Action Search Based on Dynamic Shape Volumes. In: Li, S., et al. Advances in Multimedia Modeling. Lecture Notes in Computer Science, vol 7733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35728-2_10
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DOI: https://doi.org/10.1007/978-3-642-35728-2_10
Publisher Name: Springer, Berlin, Heidelberg
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