Spectral Graph Reduction for Efficient Image and Streaming Video Segmentation

By Fabio Galasso, Margret Keuper, Thomas Brox, Bernt Schiele. 2014

86 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

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Citations in the corpus

Robust video segment proposals with painless occlusion handling (2015, methodology): “We compare our result to two state-of-art coarse-to-fine hierarchical video segmentation algorithms [19] and [15].”
Motion Trajectory Segmentation via Minimum Cost Multicuts (2015, methodology): “The current state-of-the art is again defined by methods based on spectral clustering [17, 23, 24].”
Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering (2014, methodology): “Further, we discuss the integration of learned must-link constraints via graph reduction techniques [38, 16] and learning and inference strategies.”
Long-Term Image Boundary Extrapolation (2016, background): “Video segmentation as the task of finding consistent spatio-temporal boundaries in a video volume has received significant attention over the last years [6, 18, 7, 2], as it provides an initial analysis and abstraction for further processing.”
Long-Term Image Boundary Prediction (2016, background): “…segmentation as the task of finding consistent spatio-temporal boundaries in a video volume has received significant attention over the last years (Galasso et al. 2014; Ochs, Malik, and Brox 2014; Galasso et al. 2013; Chang, Wei, and Fisher 2013), as it provides an initial analysis and…”
STFCN: Spatio-Temporal FCN for Semantic Video Segmentation (2016, methodology): “This field includes clustering algorithms such as k-means and mean-shift [31], or graph-based algorithms [12,18,23,47].”