Salient motion detection through state controllability
Salient motion detection is a challenging task especially when the motion is obscured by dynamic background motion. Salient motion is characterized by its consistency while the non-salient background motion typically consists of dynamic motion such as fog, waves, fire etc. In this paper, we present...
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sg-ntu-dr.10356-984122020-05-28T07:18:56Z Salient motion detection through state controllability Muthuswamy, Karthik Rajan, Deepu School of Computer Engineering IEEE International Conference on Acoustics, Speech and Signal Processing (2012 : Kyoto, Japan) DRNTU::Engineering::Computer science and engineering Salient motion detection is a challenging task especially when the motion is obscured by dynamic background motion. Salient motion is characterized by its consistency while the non-salient background motion typically consists of dynamic motion such as fog, waves, fire etc. In this paper, we present a novel framework for identifying salient motion by modelling the video sequence as a linear dynamic system and using controllability of states to estimate salient motion. The proposed saliency detection algorithm is tested on a challenging benchmark video dataset and the performance is compared with other state-of-the-art algorithms. The results of the comparison indicate that the proposed algorithm demonstrates superior performance when compared to other state-of-the-art methods and with higher computational efficiency. 2013-09-09T06:55:03Z 2019-12-06T19:54:58Z 2013-09-09T06:55:03Z 2019-12-06T19:54:58Z 2012 2012 Conference Paper https://hdl.handle.net/10356/98412 http://hdl.handle.net/10220/13396 10.1109/ICASSP.2012.6288167 en © 2012 IEEE. |
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DRNTU::Engineering::Computer science and engineering Muthuswamy, Karthik Rajan, Deepu Salient motion detection through state controllability |
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Salient motion detection is a challenging task especially when the motion is obscured by dynamic background motion. Salient motion is characterized by its consistency while the non-salient background motion typically consists of dynamic motion such as fog, waves, fire etc. In this paper, we present a novel framework for identifying salient motion by modelling the video sequence as a linear dynamic system and using controllability of states to estimate salient motion. The proposed saliency detection algorithm is tested on a challenging benchmark video dataset and the performance is compared with other state-of-the-art algorithms. The results of the comparison indicate that the proposed algorithm demonstrates superior performance when compared to other state-of-the-art methods and with higher computational efficiency. |
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School of Computer Engineering |
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School of Computer Engineering Muthuswamy, Karthik Rajan, Deepu |
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Conference or Workshop Item |
author |
Muthuswamy, Karthik Rajan, Deepu |
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Muthuswamy, Karthik |
title |
Salient motion detection through state controllability |
title_short |
Salient motion detection through state controllability |
title_full |
Salient motion detection through state controllability |
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Salient motion detection through state controllability |
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Salient motion detection through state controllability |
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salient motion detection through state controllability |
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2013 |
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https://hdl.handle.net/10356/98412 http://hdl.handle.net/10220/13396 |
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