PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

Action recognition based on shape features and their correlation

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents an approach for action recognition based on binary silhouette sequences extracted from consecutive frames of a video. It uses shape descriptors and correlation coefficient to represent and match entire sequences, regardless the number of frames. Each set of binary silhouettes corresponds to one action, such as jumping or waving. The paper provides experimental results on the use of the proposed approach and four shape description algorithms, namely the Two-Dimensional Fourier Descriptor, Generic Fourier Descriptor, Point Distance Histogram and UNL-Fourier Descriptor. The results are analysed in terms of the highest classification accuracy and the smallest shape descriptor size.
Rocznik
Strony
11--18
Opis fizyczny
Bibliogr. 15 poz., rys., tab.
Twórcy
  • Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland
Bibliografia
  • [1] Vishwakarma, S., Agrawal, A.: A survey on activity recognition and behaviour understanding in video surveillance. The Visual Computer 29, 983–1009, 2012.
  • [2] Borges, P.V.K., Conci, N., Cavallaro, A.: Video-based human behavior understanding: A survey. IEEE Transactions on Circuits and Systems for Video Technology 23, 1993–2008, 2013.
  • [3] Junejo, I. N., Junejo, K. N., Aghbari, Z. A.: Silhouette-based human action recognition using saxshapes. The Visual Computer 30, 259–269, 2014.
  • [4] Goudelis, G., Karpouzis, K., Kollias, S.: Exploring trace transform for robust human action recognition. Pattern Recognition 46, 3238–3248, 2013.
  • [5] Baysal, S., Kurt, M. C., Duygulu, P.: Recognizing human actions using key poses. In: 20th International Conference on Pattern Recognition, pp. 1727–1730, 2010.
  • [6] Liu, L., Shao, L., Zhen, X., Li, X.: Learning discriminative key poses for action recognition. IEEE Transactions on Cybernetics 43, 1860–1870, 2013.
  • [7] Chaaraoui, A. A., Climent-Pérez, P., Flórez-Revuelta, F.: Silhouette-based human action recognition using sequences of key poses. Pattern Recognition Letters 34, 1799 – 1807, 2013.
  • [8] Gorelick, L., Blank, M., Shechtman, E., Irani, M., Basri, R.: Actions as spacetime shapes. Transactions on Pattern Analysis and Machine Intelligence 29, 2247–2253, 2007.
  • [9] Kukharev, G.: Digital Image Processing and Analysis (in Polish). SUT Press, 1998.
  • [10] Zhang, D., Lu, G.: Review of shape representation and description techniques. Pattern Recognition 37, 1-19, 2004.
  • [11] Yang, M., Kpalma, K., Ronsin, J: A survey of shape feature extraction techniques. In: Yin, P.- Y. (Ed.), Pattern Recognition, pp. 43-90. I-Tech, Vienna, Austria, 2008
  • [12] Frejlichowski, D.: Analysis of Four Polar Shape Descriptors Properties in an Exemplary Application. In: Bolc, L. et al. (Eds.) ICCVG 2010, Part 1. LNCS, vol. 6374, pp. 376-383, 2010.
  • [13] Frejlichowski, D.: Analiza ogólnego kształtu obiektów wydobytych z obrazów cyfrowych rozpoznawanych z użyciem deskryptora PDH (in Polish). Metody Informatyki Stosowanej, 1/2009, 5-13, 2009.
  • [14] Rauber, T.W.: Two dimensional shape description. Technical report, Universidade Nova de Lisboa, Lisoba, Portugal, 1994.
  • [15] Blank, M., Gorelick, L., Shechtman, E., Irani, M., Basri, R.: Actions as spacetime shapes. In: The Tenth IEEE International Conference on Computer Vision, pp. 1395–1402, 2005
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0a627b05-8f13-471c-b7ec-4695cafeb0bc
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.