Boundary connectedness-based salient video object segmentation

Hiba Ramadan; Hamid Tairi

doi:10.1117/1.JEI.27.5.051206

9 February 2018 Boundary connectedness-based salient video object segmentation

Hiba Ramadan, Hamid Tairi

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Journal of Electronic Imaging, Vol. 27, Issue 5, 051206 (February 2018). https://doi.org/10.1117/1.JEI.27.5.051206

Abstract

One of the most challenging tasks in computer vision is to emulate human cognitive ability to extract the salient object in a scene. We tackle the task of unsupervised salient video object segmentation using boundary connectedness and space-time salient regions. First, boundary prior measure is used to separate salient regions detected in both space and time. Then, background-foreground regions connectedness is computed and combined with appearance model via an iterative energy minimization framework to segment the salient moving object. For temporal consistency, the segmentation result of the current frame is used in addition to the optical flow and the boundary prior to segmenting the next frame. The experiments show a good performance of our algorithm for salient video object segmentation on benchmark datasets even in the presence of different challenges.

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Hiba Ramadan and Hamid Tairi "Boundary connectedness-based salient video object segmentation," Journal of Electronic Imaging 27(5), 051206 (9 February 2018). https://doi.org/10.1117/1.JEI.27.5.051206

Received: 26 September 2017; Accepted: 19 January 2018; Published: 9 February 2018

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KEYWORDS

Image segmentation

Video

Optical flow

Image processing algorithms and systems

Binary data

Motion models

Visualization

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