Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios
Moving target detection (MTD) is a crucial task in computer vision applications. In this paper, we investigate the problem of detecting moving targets in infrared (IR) surveillance video sequences captured using a steady camera in a maritime setting. For this purpose, we employ robust principal comp...
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| Format: | Article |
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MDPI AG
2023-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/14/6334 |
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| author | Osvaldo Pulpito Nicola Acito Marco Diani Gabriele Ferri Raffaele Grasso Dimitris Zissis |
| author_facet | Osvaldo Pulpito Nicola Acito Marco Diani Gabriele Ferri Raffaele Grasso Dimitris Zissis |
| author_sort | Osvaldo Pulpito |
| collection | DOAJ |
| description | Moving target detection (MTD) is a crucial task in computer vision applications. In this paper, we investigate the problem of detecting moving targets in infrared (IR) surveillance video sequences captured using a steady camera in a maritime setting. For this purpose, we employ robust principal component analysis (RPCA), which is an improvement of principal component analysis (PCA) that separates an input matrix into the following two matrices: a low-rank matrix that is representative, in our case study, of the slowly changing background, and a sparse matrix that is representative of the foreground. RPCA is usually implemented in a non-causal batch form. To pursue a real-time application, we tested an online implementation, which, unfortunately, was affected by the presence of the target in the scene during the initialization phase. Therefore, we improved the robustness by implementing a saliency-based strategy. The advantages offered by the resulting technique, which we called “saliency-aided online moving window RPCA” (S-OMW-RPCA) are the following: RPCA is implemented online; along with the temporal features exploited by RPCA, the spatial features are also taken into consideration by using a saliency filter; the results are robust against the condition of the scene during the initialization. Finally, we compare the performance of the proposed technique in terms of precision, recall, and execution time with that of an online RPCA, thus, showing the effectiveness of the saliency-based approach. |
| first_indexed | 2024-03-11T00:40:39Z |
| format | Article |
| id | doaj.art-05c28d41c4824036a40cc24311ef9b87 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T00:40:39Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-05c28d41c4824036a40cc24311ef9b872023-11-18T21:16:14ZengMDPI AGSensors1424-82202023-07-012314633410.3390/s23146334Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime ScenariosOsvaldo Pulpito0Nicola Acito1Marco Diani2Gabriele Ferri3Raffaele Grasso4Dimitris Zissis5Department of Information Engineering, University of Pisa, 56122 Pisa, ItalyDepartment of Information Engineering, University of Pisa, 56122 Pisa, ItalyItalian Naval Academy, Italian Navy, 57127 Livorno, ItalyNATO Science and Technology Organization, Centre for Maritime Research and Experimentation, 19126 La Spezia, ItalyNATO Science and Technology Organization, Centre for Maritime Research and Experimentation, 19126 La Spezia, ItalyDepartment of Product & Systems Design Engineering, University of the Aegean, A 1.7.1 Hermoupoli, GR84100 Syros, GreeceMoving target detection (MTD) is a crucial task in computer vision applications. In this paper, we investigate the problem of detecting moving targets in infrared (IR) surveillance video sequences captured using a steady camera in a maritime setting. For this purpose, we employ robust principal component analysis (RPCA), which is an improvement of principal component analysis (PCA) that separates an input matrix into the following two matrices: a low-rank matrix that is representative, in our case study, of the slowly changing background, and a sparse matrix that is representative of the foreground. RPCA is usually implemented in a non-causal batch form. To pursue a real-time application, we tested an online implementation, which, unfortunately, was affected by the presence of the target in the scene during the initialization phase. Therefore, we improved the robustness by implementing a saliency-based strategy. The advantages offered by the resulting technique, which we called “saliency-aided online moving window RPCA” (S-OMW-RPCA) are the following: RPCA is implemented online; along with the temporal features exploited by RPCA, the spatial features are also taken into consideration by using a saliency filter; the results are robust against the condition of the scene during the initialization. Finally, we compare the performance of the proposed technique in terms of precision, recall, and execution time with that of an online RPCA, thus, showing the effectiveness of the saliency-based approach.https://www.mdpi.com/1424-8220/23/14/6334automatic surveillancereal timemoving target detectionmaritime scenarionaval targetsinfrared images |
| spellingShingle | Osvaldo Pulpito Nicola Acito Marco Diani Gabriele Ferri Raffaele Grasso Dimitris Zissis Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios Sensors automatic surveillance real time moving target detection maritime scenario naval targets infrared images |
| title | Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios |
| title_full | Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios |
| title_fullStr | Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios |
| title_full_unstemmed | Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios |
| title_short | Saliency-Aided Online RPCA for Moving Target Detection in Infrared Maritime Scenarios |
| title_sort | saliency aided online rpca for moving target detection in infrared maritime scenarios |
| topic | automatic surveillance real time moving target detection maritime scenario naval targets infrared images |
| url | https://www.mdpi.com/1424-8220/23/14/6334 |
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