Bio-inspired Boosting for Moving Objects Segmentation [chapter]

Isabel Martins, Pedro Carvalho, Luís Corte-Real, José Luis Alba-Castro
2016 Lecture Notes in Computer Science  
Developing robust and universal methods for unsupervised segmentation of moving objects in video sequences has proved to be a hard and challenging task. State-of-the-art methods show good performance in a wide range of situations, but systematically fail when facing more challenging scenarios. Lately, a number of image processing modules inspired in biological models of the human visual system have been explored in different areas of application. This paper proposes a bio-inspired boosting
more » ... d to address the problem of unsupervised segmentation of moving objects in video that shows the ability to overcome some of the limitations of widely used state-of-the-art methods. An exhaustive set of experiments was conducted and a detailed analysis of the results, using different metrics, revealed that this boosting is more significant when challenging scenarios are faced and state-of-the-art methods tend to fail.
doi:10.1007/978-3-319-41501-7_45 fatcat:5wjheb2m3bhtbg2qh2g5vlmhzu