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2021 | OriginalPaper | Chapter

4. Tracking of Domestic Animals in Thermal Videos by Tensor Decompositions

Authors : Ivo Draganov, Rumen Mironov

Published in: New Approaches for Multidimensional Signal Processing

Publisher: Springer Singapore

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Abstract

In this paper, we present a comparative analysis of the performance of the Tucker-ALS, CP-ALS, Tucker-ADAL, and the HoRPCA-S tensor decomposition algorithms, applied for tracking of domestic animals in video. Decomposition and full processing time, detection rate, precision, and F-measure are the evaluating parameters revealing the efficiency of each algorithm. Promising results suggest the applicability of the investigated decompositions but also demonstrate particular differences among them in terms of decomposition time and detection rate. In order to increase the detection rate of systems of parallel type employing multiple decomposition algorithms we propose a score fusion with fair voting which performs better than some of the tested algorithms alone.

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Metadata
Title
Tracking of Domestic Animals in Thermal Videos by Tensor Decompositions
Authors
Ivo Draganov
Rumen Mironov
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-4676-5_4