Grouping in the normalized cut framework
Research output: Contribution to journal › Conference article › Research › peer-review
In this paper, we study low-level image segmentation in the normalized cut framework proposed by Shi and Malik (1997). The goal is to partition the image from a big picture point of view. Perceptually signicant groups are detected rst while small variations and details are treated later. Dierent image features-intensity, color, texture, con-tour continuity, motion and stereo disparity are treated in one uniform framework. We suggest directions for intermediate-level grouping on the output of this low-level segmentation.
Original language | English |
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Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Pages (from-to) | 155-164 |
Number of pages | 10 |
ISSN | 0302-9743 |
DOIs | |
Publication status | Published - 1999 |
Externally published | Yes |
Event | International Workshop on Shape, Contour and Grouping in Computer Vision - Palermo, Sicily, Italy Duration: 26 May 1998 → 29 May 1998 |
Conference
Conference | International Workshop on Shape, Contour and Grouping in Computer Vision |
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Country | Italy |
City | Palermo, Sicily |
Period | 26/05/1998 → 29/05/1998 |
Sponsor | GE Center For Research and Development, The Centro Interdipartimentale Tecnologie della Conoscenza (C.I.T.C.), Palermo, The National Science Foundation, University, Palermo, Sicily |
Bibliographical note
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1999.
ID: 302060460