Foreground Segmentation for Moving Cameras under Low Illumination Conditions
W Wang, W Li, X Yin, Y Liu, M Zhang - International Conference on …, 2016 - scitepress.org
W Wang, W Li, X Yin, Y Liu, M Zhang
International Conference on Pattern Recognition Applications and Methods, 2016•scitepress.orgA foreground segmentation method, including image enhancement, trajectory classification
and object segmentation, is proposed for moving cameras under low illumination conditions.
Gradient-field-based image enhancement is designed to enhance low-contrast images. On
the basis of the dense point trajectories obtained in long frames sequences, a simple and
effective clustering algorithm is designed to classify foreground and background trajectories.
By combining trajectory points and a marker-controlled watershed algorithm, a new type of …
and object segmentation, is proposed for moving cameras under low illumination conditions.
Gradient-field-based image enhancement is designed to enhance low-contrast images. On
the basis of the dense point trajectories obtained in long frames sequences, a simple and
effective clustering algorithm is designed to classify foreground and background trajectories.
By combining trajectory points and a marker-controlled watershed algorithm, a new type of …
A foreground segmentation method, including image enhancement, trajectory classification and object segmentation, is proposed for moving cameras under low illumination conditions. Gradient-field-based image enhancement is designed to enhance low-contrast images. On the basis of the dense point trajectories obtained in long frames sequences, a simple and effective clustering algorithm is designed to classify foreground and background trajectories. By combining trajectory points and a marker-controlled watershed algorithm, a new type of foreground labeling algorithm is proposed to effectively reduce computing costs and improve edge-preserving performance. Experimental results demonstrate the promising performance of the proposed approach compared with other competing methods.
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