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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Uncertain Region Identification for Stereoscopic Foreground Cutout
verfasst von : Taotao Yang, Shuaicheng Liu, Chao Sun, Zhengning Wang, Bing Zeng
Erschienen in: Image and Graphics
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Abstract
This paper presents a method that automatically segments the foreground objects for stereoscopic images. Given a stereo pair, a disparity map can be estimated, which encodes the depth information. Objects that stay close to the camera are considered as foreground while regions with larger depths are deemed as background. Although the raw disparity map is usually noisy, incomplete, and inaccurate, it facilitates an automatic generation of trimaps for both views, where the images are partitioned into three regions: definite foreground, definite background, and uncertain region. Our job is now reduced to labelling of pixels in the uncertain region, in which the number of unknown pixels has been decreased largely. We propose to use an MRF based energy minimization for labelling the unknown pixels, which involves both local and global color probabilities within and across views. Results are evaluated by objective metrics on a ground truth stereo segmentation dataset, which validates the effectiveness of our proposed method.