Abstract
In this paper two new schemes are proposed for fusion of the results from video decomposition by Robust Principal Component Analysis and Non-negative Matrix Factorization with the aim of detecting moving objects over stationary background. The schemes use the logical OR and AND operators on a pixel basis over the binary outputs of the base decomposition algorithms. Experimental results from testing with videos, containing natural scenes with humans and vehicles, reveal the applicability of both schemes with higher Detection Rate for the OR operator and considerably higher Precision for the AND operator. The latter gets the highest F-measure of 0.8168 and is considered applicable in various systems where higher reliability is sought. Execution times for all tested implementations are practical, although allowing further optimization, which renders the proposed algorithms applicable in a wide set of applications.
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Acknowledgements
This work was supported by the National Science Fund of Bulgaria: KP-06-H27/16 “Development of efficient methods and algorithms for tensor-based processing and analysis of multidimensional images with application in interdisciplinary areas”.
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Draganov, I., Mironov, R. (2022). Object Motion Detection in Video by Fusion of RPCA and NMF Decompositions. In: Kountchev, R., Mironov, R., Nakamatsu, K. (eds) New Approaches for Multidimensional Signal Processing. Smart Innovation, Systems and Technologies, vol 270. Springer, Singapore. https://doi.org/10.1007/978-981-16-8558-3_2
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DOI: https://doi.org/10.1007/978-981-16-8558-3_2
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