Improved Cut-Based Foreground Identification

Summary

This paper shows how to make graph based schemes tractable and useful, and why the normalized cut framework is appealing because it looks at an image or an image sequence from a global perspective.

Keywords

Computer science, Perspective (graphical), Artificial intelligence, Pixel, Computer vision

References

A Fast Segmentation Algorithm RevisitedSharat Chandran, Kamlesh K. Madhesiya — 2002
Real-time adaptive background segmentationDavid Butler, S. Sridharan, V. Michael Bove — 2003
Background-foreground segmentation based on dominant motion estimation and static segmentationYixing Huang, Dietrich Paulus, H. Niemann — 2000
Motion segmentation and tracking using normalized cutsJianbo Shi, Jitendra Malik — 1998
A Survey of Spatio-Temporal Grouping TechniquesRémi Mégret, Daniel DeMenthon — 2002
Globally optimal regions and boundariesIan H. Jermyn, Hiroshi Ishikawa — 1999
Fast multiscale image segmentationE. Sharon, Achi Brandt, Ronen Basri — 2000
Evaluation of local models of dynamic backgroundsRobert Pless, John D. Larson, S. Siebers — 2003
Image Segmentation with Ratio CutSong Wang, Jeffrey Mark Siskind — 2003
Image segmentation using local variationPedro F. Felzenszwalb, D.P. Huttenlocher — 1998
Spectral grouping using the Nystrom methodCharless C. Fowlkes, Serge Belongie, Fan Chung — 2004
Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning AutomataSudeep Sarkar, Padmanabhan Soundararajan — 2000
Video object segmentation and tracking for content-based video codingJinyun Zhou, Ee Ping Ong, C.C. Ko — 2000
Image segmentation by nested cutsOlga Veksler — 2000
Detection of moving objects in video using a robust motion similarity measureHieu Thanh Nguyen, Marcel Worring, A. Dev — 2000
An Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image SegmentationZhenyu Wu, Richard M. Leahy — 1993
Layered motion segmentation and depth ordering by tracking edgesPaul Smith, Tom Drummond, Roberto Cipolla — 2004
Normalized cuts and image segmentationJianbo Shi, Jitendra Malik — 1997
A new graph-theoretic approach to clustering and segmentationMassimiliano Pavan, Marcello Pelillo — 2003
Recovering human body configurations: combining segmentation and recognitionGiulio Mori, Xiaofeng Ren, Alexei A. Efros — 2004

Cited by

High-Throughput Biomarker Segmentation on Ovarian Cancer Tissue Microarrays via Hierarchical Normalized CutsAndrew Janowczyk, Sharat Chandran, Rajesh R. Singh — 2012
Automatic Detection and Classification of Tumor Infiltrating LymphocytesA. Janowczyk, S. Chandran — 2013

Related papers

Color Image Segmentation Based on Mean Shift and Normalized CutsWenbing Tao, Hai Jin, Yimin Zhang — 2007
Image Segmentation Based on Fast Normalized CutChunlan Zhao — 2015
An Image Segmentation Approach Based on Split-Combining Algorithm and Normalized Cut MethodLifang Chen — 2011
Fast supervised texture detection algorithmZhang Zai-mei — 2007
Interactive foreground segmentation method using mean shift and graph cutsYuan Tian, Tao Guan, Cheng Wang — 2009
Video cut detection using block based histogram differences in RGB color spaceG. G. Lakshmi Priya, S. Domnic — 2010
An improved automatic image sequencing algorithmJuan Wang — 2009
An improved image segmentation algorithm base on normalized cutQi Xi — 2010
Color Image Segmentation of Foreground and Background based on Mean Shift AlgorithmLiang jingmin - — 2012
An Improved Grabcut Image Segmentation MethodYI Cong-con — 2014