The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition
Open accessAbstract
In this paper we introduce a template-based method for recognizing human actions called action MACH. Our approach is based on a maximum average correlation height (MACH) filter. A common limitation of template-based methods is their inability to generate a single template using a collection of examples. MACH is capable of capturing intra-class variability by synthesizing a single Action MACH filter for a given action class. We generalize the traditional MACH filter to video (3D spatiotemporal volume), and vector valued data. By analyzing the response of the filter in the frequency domain, we avoid the high computational cost commonly incurred in template-based approaches. Vector valued data is analyzed using the Clifford Fourier transform, a generalization of the Fourier transform intended for both scalar and vector-valued data. Finally, we perform an extensive set of experiments and compare our method with some of the most recent approaches in the field by using publicly available datasets, and two new annotated human action datasets which include actions performed in classic feature films and sports broadcast television.
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Cites
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RGBD-HuDaAct: A color-depth video database for human daily activity recognition
Ni, B., Wang, G., & Moulin, P. (2011) · 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) · doi:10.1109/iccvw.2011.6130379 · Cited by 304
Khan, M. A., Javed, K., Khan, S. A., Saba, T., Habib, U., Khan, J. A., & Abbasi, A. A. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08806-9 · Cited by 277
Objects2action: Classifying and Localizing Actions without Any Video Example
Jain, M., Gemert, J. C. V., Mensink, T., & Snoek, C. G. M. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.521 · Cited by 142
(2016) · MPG.PuRe (Max Planck Society) · Cited by 107
Metadata
- Authors
- Rodriguez, M. D., Ahmed, J., & Shah, M.
- Venue
- 2008 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2008-06
- Pages
- 1-8
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2101194540
- Cited by
- 1,223
- References
- 1
- FWCI
- 31.79
- Type
- conference paper
- Language
- en
- Open access
- green
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