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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Main Authors: | , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/98412 http://hdl.handle.net/10220/13396 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | 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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