102
Views
8
CrossRef citations to date
0
Altmetric
Articles

Robust Human Action Recognition Using AREI Features and Trajectory Analysis from Silhouette Image Sequence

, &

REFERENCES

  • T. Bouwmans , F. Porikli , B. Hoferlin , and A. Vacavant , Background Modeling and Foreground Detection for Video Surveillance . Florida: CRC Press, 2014. ISBN- 1482205378, 9781482205374.
  • J. Man and B. Bhanu , “Individual recognition using gait energy image,” IEEE Tran. Pattern Anal. Mach. Intell. , Vol. 28, no. 2, pp. 316–22, Feb. 2006.
  • F. Bobic and J Davis , “The recognition of human movement using Temporal Templates,” IEEE Tran. Pattern Anal. Mach. Intell. , Vol. 23, no. 3, pp. 257–67, Mar. 2001.
  • J. Davis . “Hierarchical motion history image for recognizing human motion,” in IEEE Workshop on Detection and Recognition of Events in the Video , Vancouver , 2001.
  • V. Kellokumpu , G. Zhao , and M. Pietikinen , “Human activity recognition using a dynamic texture based method,” in The British Machine Vision Conference , Leeds , 2008.
  • U. Mahbub , H. Imtiaz , and M.R. Ahad , “An optical flow based approach for action recognition,” in Proceedings of International Conference of Computer and Information Technology (ICCIT) , 2011, pp. 646–51.
  • S. Maity , A. Chakrabarti , and D. Bhattacharjee , “A novel approach for human action recognition from silhouette images,” IETE J. Res . Vol. 63, Nov. 2016. doi:dx.doi.org/10.1080/03772063.2016.1242383
  • J. K. Aggarwal and M. S. Ryoo , “Human activity analysis: A review,” ACM Comput. Survey (CSUR), Vol. 43, no. 3, 16, Apr. 2011.
  • A. A. Chaaraoui , P. C. Perez , and F. F. Revuelta , “Silhouette-based Human action recognition using sequences of key poses,” Pattern Recogn. Lett. , 34, pp. 17991–807, Feb. 2013.
  • J. Cheng , H. Liu , F. Wang , H. Li , and C. Zhu , “Silhouette analysis for human action recognition based on supervised temporal t-SNE and incremental learning,” IEEE Trans. Image Process. , Vol. 24, no. 10, pp. 3203–17, Oct. 2015.
  • D. Wu and L. Shao , “Silhouette Analysis-based action recognition via exploiting human poses,” IEEE Trans. Circ. Syst. Video Technol. , Vol. 23, no. 2, pp. 236–43, Feb. 2013.
  • S. A. Rahman , I. Song , M. K. H. Leung , I. Lee , and K. Lee , “Fast action recognition using negative space features,” Expert Syst. Appl. , 41, pp. 574–87, Feb. 2014.
  • D. K. Vishwakarma and R. Kapoor , “Integrated approach for human action recognition using edge spatial distribution, direction pixel and R-transform,” Adv. Robotics , Vol. 29, no. 23, pp. 1551–61, Jun. 2015.
  • J. Cheng , H. Liu , and H. Li , “Silhouette analysis for human action recognition based on maximum spatio-temporal dissimilarity embedding,” Mach. Vis. Appl. , Vol. 25, pp. 1007–18, Aug. 2014.
  • A. A. Chaaraoui and F. Flórez-Revuelta , “A low-dimensional radial silhouette-based feature for fast human action recognition fusing multiple views,” Int. Sch. Res. Notices , 2014, 547069, Apr. 2014.
  • M. Blank , L. Gorelick , E. Shechtman , M. Irani , and R. Basri , “Actions as space-time shapes. Computer Vision,” in Tenth IEEE International Conference on Computer Vision (ICCV), Beiging, Dec. 2005, pp. 1395–1402. doi:10.1109/ICCV.
  • S. Singh , S. A. Velastin , and H. Ragheb , “MuHAVi: A multi-camera human action video dataset for the evaluation of action recognition methods,” in Proceeding of IEEE International Conference on Advanced Video and Signal Based Surveillance, ser. AVSS. 10. Washington, DC , Aug. 2010, pp. 48–55.
  • A. Eweiwi , S. Cheema , C. Thurau , and C. Bauckhage , “Temporal key poses for human action recognition,” in IEEE International Conference on Computer Vision Work-shops (ICCV Workshops) , Barcelona , Aug. 2011, pp. 1310–17.
  • J. Hernandez , A. Montemayor , J. Pantrigo , and A. Sanchez . “Human action recognition based on tracking features,” in Foundations of Natural and Artificial Computation, Lecture Notes in Computer Science, Vol. 6686. 2011, pp. 471–80. Berlin, Heidelberg: Springer.
  • S. Cheema , A. Eweiwi , C. Thurau , and C. Bauckhage , “Action recognition by learning discriminative key poses,” in IEEE International Conference on Computer Vision Workshops (ICCV Workshops) , Barcelona, 2011, pp. 1302–09.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.