Abstract
Surveillance systems in shopping malls or supermarkets are usually used for detecting abnormal behavior. We used the distributed video cameras system to design digital shopping assistants which assess the behavior of customers while shopping, detect when they need assistance, and offer their support in case there is a selling opportunity. In this paper we propose a system for analyzing human behavior patterns related to products interaction, such as browse through a set of products, examine, pick products, try on, interact with the shopping cart, and look for support by waiving one hand. We used the Kinect sensor to detect the silhouettes of people and extracted discriminative features for basic action detection. Next we analyzed different classification methods, statistical and also spatio-temporal ones, which capture relations between frames, features, and basic actions. By employing feature level fusion of appearance and movement information we obtained an accuracy of 80% for the mentioned six basic actions.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Popa, M.C., Rothkrantz, L.J.M., Yang, Z., Wiggers, P., Braspenning, R., Shan, C.: Analysis of Shopping Behavior based on Surveillance System. In: 2010 IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC 2010), Istanbul, Turkey (2010)
Popa, M.C., Gritti, T., Rothkrantz, L.J.M., Shan, C., Wiggers, P.: Detecting Customers’ Buying Events on a Real-Life Database. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds.) CAIP 2011, Part I. LNCS, vol. 6854, pp. 17–25. Springer, Heidelberg (2011)
Microsoft Corp. Redmond WA. Kinect for Xbox 360
Moeslund, T.B., Hilton, A., Kruger, V.: A Survey of Advances in Vision-based Human Motion Capture and Analysis. Computer Vision and Image Understanding (2006)
Akita, K.: Image sequence analysis of real world human motion. Pattern Recognition 17(1), 73–83 (1984)
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: CVPR (2011)
Bobick, A.F., Davis, J.W.: The recognition of human movement using temporal templates. IEEE Trans. PAMI (2001)
Ekinci, M., Gedikli, E.: Silhouette Based Human Motion Detection and Analysis for Real-Time Automated Video Surveillance. Turkish Journal of Electrical Engineering and Computer Sciences 13(2), 199–230 (2005)
Jiang, H., Drew, M.S., Li, Z.-N.: Action Detection in Cluttered Video with Successive Convex Matching. IEEE Transactions on Circuits and Systems for Video Technology 20(1) (2010)
Haritaoglu, I., Cutler, R., Harwood, D., Davis, L.S.: Detection of People Carrying Objects Using Silhouettes. In: International Conference on Computer Vision, Corfu, Greece (1999)
Moore, D.J., Essa, I.A., Hayes, M.H.: Exploiting Human Actions and Object Context for Recognition Tasks. In: IEEE International Conference on Computer Vision, Corfu, Greece (1999)
Brand, M., Oliver, N., Pentland, A.: Coupled Hidden Markov Models for Complex Action Recognition. In: Proceedings of IEEE Computer Vision and Pattern Recognition (1996)
Yamato, J., Ohya, J., Ishii, K.: Recognizing Human Action in Time-Sequential Images using Hidden Markov Model. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 379–385 (1992)
Schindler, K., Van Gool, L.: Action Snippets: How Many Frames Does Human Action Recognition Require? In: IEEE Computer Society Conference on Computer Vision (2007)
Shüldt, C., Laptev, I., Caputo, B.: Recognizing Human Actions: A Local SVM Approach. In: Proceedings of the 17th International Conference on Pattern Recognition (2004)
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) (2007)
Weinland, D., Ronfard, R., Boyer, E.: Free Viewpoint Action Recognition using Motion History Volumes. Computer Vision Image Understanding 104(2), 249–257 (2006)
Prismall, S.P.: Object reconstruction by moments extended to moving sequences, PhD thesis, Department Electronic and Computer Science, University of Southampton (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Popa, M., Kemal Koc, A., Rothkrantz, L.J.M., Shan, C., Wiggers, P. (2012). Kinect Sensing of Shopping Related Actions. In: Wichert, R., Van Laerhoven, K., Gelissen, J. (eds) Constructing Ambient Intelligence. AmI 2011. Communications in Computer and Information Science, vol 277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31479-7_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-31479-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31478-0
Online ISBN: 978-3-642-31479-7
eBook Packages: Computer ScienceComputer Science (R0)