Skip to main content
main-content

Tipp

Weitere Kapitel dieses Buchs durch Wischen aufrufen

2018 | OriginalPaper | Buchkapitel

Silhouette-Based Action Recognition Using Simple Shape Descriptors

verfasst von: Katarzyna Gościewska, Dariusz Frejlichowski

Erschienen in: Computer Vision and Graphics

Verlag: Springer International Publishing

share
TEILEN

Abstract

This paper presents human action recognition method based on silhouette sequences and simple shape descriptors. The proposed solution uses single scalar shape measures to represent each silhouette from an action sequence. Scalars are then combined into a vector that represents the entire sequence. In the following step, vectors are transformed into sequence representations and matched with the use of leave-one-out cross-validation technique and selected similarity or dissimilarity measure. Additionally, action sequences are pre-classified using the information about centroid trajectory into two subgroups—actions that are performed in place and actions during which a person moves in the frame. The average percentage accuracy is 80%—the result is very satisfactory taking into consideration the very small amount of data used. The paper provides information on the approach, some key definitions as well as experimental results.
Literatur
1.
Zurück zum Zitat Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90–126 (2006) CrossRef Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90–126 (2006) CrossRef
2.
Zurück zum Zitat Poppe, R.: A survey on vision-based human action recognition. Image Vis. Comput. 28(6), 976–990 (2010) CrossRef Poppe, R.: A survey on vision-based human action recognition. Image Vis. Comput. 28(6), 976–990 (2010) CrossRef
3.
Zurück zum Zitat Weinland, D., Ronfard, R., Boyer, E.: A survey of vision-based methods for action representation, segmentation and recognition. Comput. Vis. Image Underst. 115(2), 224–241 (2011) CrossRef Weinland, D., Ronfard, R., Boyer, E.: A survey of vision-based methods for action representation, segmentation and recognition. Comput. Vis. Image Underst. 115(2), 224–241 (2011) CrossRef
4.
Zurück zum Zitat Borges, P.V.K., Conci, N., Cavallaro, A.: Video-based human behavior understanding: a survey. IEEE Trans. Circ. Syst. Video Technol. 23(11), 1993–2008 (2013) CrossRef Borges, P.V.K., Conci, N., Cavallaro, A.: Video-based human behavior understanding: a survey. IEEE Trans. Circ. Syst. Video Technol. 23(11), 1993–2008 (2013) CrossRef
5.
Zurück zum Zitat Cheng, G., Wan, Y., Saudagar, A.N., Namuduri, K., Buckles, B.P.: Advances in human action recognition: a survey. CoRR (2015) Cheng, G., Wan, Y., Saudagar, A.N., Namuduri, K., Buckles, B.P.: Advances in human action recognition: a survey. CoRR (2015)
6.
Zurück zum Zitat Herath, S., Harandi, M., Porikli, F.: Going deeper into action recognition: a survey. Image Vis. Comput. 60, 4–21 (2017) CrossRef Herath, S., Harandi, M., Porikli, F.: Going deeper into action recognition: a survey. Image Vis. Comput. 60, 4–21 (2017) CrossRef
7.
Zurück zum Zitat Vishwakarma, S., Agrawal, A.: A survey on activity recognition and behavior understanding in video surveillance. Vis. Comput. 29(10), 983–1009 (2013) CrossRef Vishwakarma, S., Agrawal, A.: A survey on activity recognition and behavior understanding in video surveillance. Vis. Comput. 29(10), 983–1009 (2013) CrossRef
8.
Zurück zum Zitat Chaquet, J.M., Carmona, E.J., Fernández-Caballero, A.: A survey of video datasets for human action and activity recognition. Comput. Vis. Image Underst. 117(6), 633–659 (2013) CrossRef Chaquet, J.M., Carmona, E.J., Fernández-Caballero, A.: A survey of video datasets for human action and activity recognition. Comput. Vis. Image Underst. 117(6), 633–659 (2013) CrossRef
9.
Zurück zum Zitat Schuldt, C., Laptev, I., Caputo, B.: Recognizing human actions: a local SVM approach. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 32–36 (2004) Schuldt, C., Laptev, I., Caputo, B.: Recognizing human actions: a local SVM approach. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 32–36 (2004)
10.
Zurück zum Zitat Gorelick, L., Blank, M., Shechtman, E., Irani, M., Basri, R.: Actions as space-time shapes. IEEE Trans. Pattern Anal. Mach. Intell. 29(12), 2247–2253 (2007) CrossRef Gorelick, L., Blank, M., Shechtman, E., Irani, M., Basri, R.: Actions as space-time shapes. IEEE Trans. Pattern Anal. Mach. Intell. 29(12), 2247–2253 (2007) CrossRef
11.
Zurück zum Zitat 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 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
12.
Zurück zum Zitat Alp, E.C., Keles, H.Y.: Action recognition using MHI based Hu moments with HMMs. In: IEEE EUROCON 2017–17th International Conference on Smart Technologies, pp. 212–216 (2017) Alp, E.C., Keles, H.Y.: Action recognition using MHI based Hu moments with HMMs. In: IEEE EUROCON 2017–17th International Conference on Smart Technologies, pp. 212–216 (2017)
13.
Zurück zum Zitat Chen, D.Y., Shih, S.W., Liao, H.Y.M.: Human action recognition using 2-D spatio-temporal templates. In: 2007 IEEE International Conference on Multimedia and Expo, pp. 667–670 (2007) Chen, D.Y., Shih, S.W., Liao, H.Y.M.: Human action recognition using 2-D spatio-temporal templates. In: 2007 IEEE International Conference on Multimedia and Expo, pp. 667–670 (2007)
14.
Zurück zum Zitat Baysal, S., Kurt, M.C., Duygulu, P.: Recognizing human actions using key poses. In: 2010 20th International Conference on Pattern Recognition, pp. 1727–1730 (2010) Baysal, S., Kurt, M.C., Duygulu, P.: Recognizing human actions using key poses. In: 2010 20th International Conference on Pattern Recognition, pp. 1727–1730 (2010)
15.
Zurück zum Zitat Chaaraoui, A.A., Climent-Pérez, P., Flórez-Revuelta, F.: Silhouette-based human action recognition using sequences of key poses. Pattern Recogn. Lett. 34(15), 1799–1807 (2013) CrossRef Chaaraoui, A.A., Climent-Pérez, P., Flórez-Revuelta, F.: Silhouette-based human action recognition using sequences of key poses. Pattern Recogn. Lett. 34(15), 1799–1807 (2013) CrossRef
16.
Zurück zum Zitat Islam, S., Qasim, T., Yasir, M., Bhatti, N., Mahmood, H., Zia, M.: Single- and two-person action recognition based on Silhouette shape and optical point descriptors. Sig. Image Video Process. 12(5), 853–860 (2018) CrossRef Islam, S., Qasim, T., Yasir, M., Bhatti, N., Mahmood, H., Zia, M.: Single- and two-person action recognition based on Silhouette shape and optical point descriptors. Sig. Image Video Process. 12(5), 853–860 (2018) CrossRef
17.
Zurück zum Zitat Goudelis, G., Karpouzis, K., Kollias, S.: Exploring trace transform for robust human action recognition. Pattern Recogn. 46(12), 3238–3248 (2013) CrossRef Goudelis, G., Karpouzis, K., Kollias, S.: Exploring trace transform for robust human action recognition. Pattern Recogn. 46(12), 3238–3248 (2013) CrossRef
19.
20.
Zurück zum Zitat Vishwakarma, D.K., Gautam, J., Singh, K.: A robust framework for the recognition of human action and activity using spatial distribution gradients and Gabor wavelet. In: Reddy, M.S., Viswanath, K., K.M., S.P. (eds.) International Proceedings on Advances in Soft Computing, Intelligent Systems and Applications. AISC, vol. 628, pp. 103–113. Springer, Singapore (2018). https://​doi.​org/​10.​1007/​978-981-10-5272-9_​10 CrossRef Vishwakarma, D.K., Gautam, J., Singh, K.: A robust framework for the recognition of human action and activity using spatial distribution gradients and Gabor wavelet. In: Reddy, M.S., Viswanath, K., K.M., S.P. (eds.) International Proceedings on Advances in Soft Computing, Intelligent Systems and Applications. AISC, vol. 628, pp. 103–113. Springer, Singapore (2018). https://​doi.​org/​10.​1007/​978-981-10-5272-9_​10 CrossRef
23.
Zurück zum Zitat Brunelli, R., Messelodi, S.: Robust estimation of correlation with applications to computer vision. Pattern Recogn. 28(6), 833–841 (1995) CrossRef Brunelli, R., Messelodi, S.: Robust estimation of correlation with applications to computer vision. Pattern Recogn. 28(6), 833–841 (1995) CrossRef
24.
Zurück zum Zitat Yang, L., Albregtsen, F., Lønnestad, T., Grøttum, P.: Methods to estimate areas and perimeters of blob-like objects: a comparison. In: Proceedings of IAPR Workshop on Machine Vision Applications, pp. 272–276 (1994) Yang, L., Albregtsen, F., Lønnestad, T., Grøttum, P.: Methods to estimate areas and perimeters of blob-like objects: a comparison. In: Proceedings of IAPR Workshop on Machine Vision Applications, pp. 272–276 (1994)
25.
Zurück zum Zitat Yang, M., Kpalma, K., Ronsin, J.: A survey of shape feature extraction techniques. In: Yin, P.-Y. (ed.) Pattern Recognition, pp. 43–90. INTECH Open Access Publisher (2008) Yang, M., Kpalma, K., Ronsin, J.: A survey of shape feature extraction techniques. In: Yin, P.-Y. (ed.) Pattern Recognition, pp. 43–90. INTECH Open Access Publisher (2008)
Metadaten
Titel
Silhouette-Based Action Recognition Using Simple Shape Descriptors
verfasst von
Katarzyna Gościewska
Dariusz Frejlichowski
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-030-00692-1_36

Premium Partner