Learning multi-scale features for foreground segmentation

• Published in: Pattern analysis and applications : PAA Vol. 23; no. 3; pp. 1369 - 1380
• Main Authors: Lim, Long Ang, Keles, Hacer Yalim
• Format: Journal Article
• Language: English
• Published: London Springer London 01.08.2020; Springer Nature B.V
• Subjects: Algorithms; Artificial neural networks; Coders; Computer Science; Datasets; Feature extraction; Image segmentation; Machine learning; Modules; Pattern Recognition; Robustness; Short Paper; Source code; Subtraction; Feature pooling module; Foreground segmentation; Video surveillance; Convolutional neural networks; Background subtraction

Foreground segmentation algorithms aim at segmenting moving objects from the background in a robust way under various challenging scenarios. Encoder–decoder-type deep neural networks that are used in this domain recently perform impressive segmentation results. In this work, we propose a variation o...