Paper
6 July 2015 Multi-view object co-segmentation based on the mixture of links model
Dongting Hu, Yugang Li, Xiabi Liu
Author Affiliations +
Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 96310S (2015) https://doi.org/10.1117/12.2197637
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States
Abstract
We present a novel mixture of links model to segment an object observed from multiple viewpoints. Each component in this mixture represents a temporal linkage between superpixels from all the viewpoints, hence expressing the inter-view consistency. The principle goal is to find the maximum a posterior estimate of appearance models and the exact bounding-box of object in each view. To this end, the segmentation is casted as finding more comprehensive and accurate samples using the mixture of links model. In contrast to most existing multi-view co-segmentation methods that rely on time-consuming 3D information, our method only uses 2D cues to achieve faster speed without decreasing the accuracy. The experimental results confirm the effectiveness of our approach.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dongting Hu, Yugang Li, and Xiabi Liu "Multi-view object co-segmentation based on the mixture of links model", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96310S (6 July 2015); https://doi.org/10.1117/12.2197637
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KEYWORDS
3D modeling

Image segmentation

Expectation maximization algorithms

Statistical modeling

3D image processing

Image resolution

Visual process modeling

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