Abstract
A great variety of human gesture recognition methods exist in the literature, yet there is still a lack of solutions to encompass some of the challenges imposed by real life scenarios. In this document, a gesture recognition for robotic search and rescue missions in the high seas is presented. The method aims to identify shipwrecked people by recognizing the hand waving gesture sign.
We introduce a novel motion descriptor, through which high recognition accuracy can be achieved even for low resolution images. The method can be simultaneously applied to rigid object characterization, hence object and gesture recognition can be performed simultaneously.
The descriptor has a simple implementation and is invariant to scale and gesture speed. Tests, preformed on a maritime dataset of thermal images, proved the descriptor ability to reach a meaningful representation for very low resolution objects. Recognition rates with 96.3% of accuracy were achieved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kaâniche, M., Bremond, F.: Recognizing Gestures by Learning Local Motion Signatures of HOG Descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 2247–2258 (2012)
Lertniphonphan, K., Aramvith, S., Chalidabhongse, T.H.: Human action recognition using direction histograms of optical flow. In: 2011 11th International Symposium on Communications and Information Technologies (ISCIT), pp. 574–579, October 2011
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)
Laptev, I.: On space-time interest points. Int. J. Comput. Vision 64(2–3), 107–123 (2005)
Bradski, G., Davis, J.: Motion segmentation and pose recognition with motion history gradients. In: Fifth IEEE Workshop on Applications of Computer Vision, pp. 238–244 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Ferreira, A., Silva, G., Dias, A., Martins, A., Campilho, A. (2016). Motion Descriptor for Human Gesture Recognition in Low Resolution Images. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-319-27146-0_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-27146-0_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27145-3
Online ISBN: 978-3-319-27146-0
eBook Packages: Computer ScienceComputer Science (R0)