Stereo for Image-Based Rendering using Image Over-Segmentation

By C. Lawrence Zitnick, Sing Bing Kang. International Journal of Computer Vision, 2007

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Superpixels and Polygons Using Simple Non-iterative Clustering (2017, background): “After their introduction [27], several applications such as object localization [14], multi-class segmentation [15], optical flow [22], body model estimation [24], object tracking [35], and depth estimation [37] took advantage of superpixels .”
Review of Stereo Vision Algorithms: From Software to Hardware (2008, methodology): “Moreover, a stereo method specifically designed for image-based rendering is described in (Zitnick and Kang 2007).”
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods (2012, methodology): “While strikingly simple, SLIC is shown to yield state-of-the-art adherence to image boundaries on the Berkeley benchmark [ 20], and outperforms existing methods when used for segmentation on the PASCAL [7] and MSRC [24] data sets.”
Consistent Depth Maps Recovery from a Video Sequence (2009, methodology): “STEREO reconstruction of dense depth maps from naturalvideo sequences is a fundamentally important and challenging problem in computer vision.”