Online Mutual Foreground Segmentation for Multispectral Stereo Videos
Pierre-Luc St-Charles, Guillaume-Alexandre Bilodeau, Robert Bergevin

TL;DR
This paper introduces a novel iterative method for simultaneous multispectral stereo video segmentation and registration, leveraging shape and appearance cues with temporal coherence to improve object segmentation in challenging conditions.
Contribution
It presents a new approach that jointly addresses multispectral segmentation and stereo registration through alternating minimization and dynamic priors, enhancing accuracy in low contrast and complex scenes.
Findings
Effective in diverse multispectral datasets
Improves segmentation accuracy in low contrast regions
Enhances temporal coherence of segmentation results
Abstract
The segmentation of video sequences into foreground and background regions is a low-level process commonly used in video content analysis and smart surveillance applications. Using a multispectral camera setup can improve this process by providing more diverse data to help identify objects despite adverse imaging conditions. The registration of several data sources is however not trivial if the appearance of objects produced by each sensor differs substantially. This problem is further complicated when parallax effects cannot be ignored when using close-range stereo pairs. In this work, we present a new method to simultaneously tackle multispectral segmentation and stereo registration. Using an iterative procedure, we estimate the labeling result for one problem using the provisional result of the other. Our approach is based on the alternating minimization of two energy functions that…
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Taxonomy
TopicsAdvanced Image and Video Retrieval Techniques · Advanced Vision and Imaging · Medical Image Segmentation Techniques
