• Publications
  • Influence
Normalized cuts and image segmentation
  • Jianbo Shi, J. Malik
  • Mathematics, Computer Science
  • Proceedings of IEEE Computer Society Conference…
  • 17 June 1997
TLDR
This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups. Expand
Good features to track
TLDR
A feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world are proposed. Expand
Normalized Cuts and Image Segmentation
  • Jianbo Shi, J. Malik
  • Mathematics, Computer Science
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 1 August 2000
TLDR
This work treats image segmentation as a graph partitioning problem and proposes a novel global criterion, the normalized cut, for segmenting the graph, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups. Expand
Multiclass spectral clustering
  • Stella X. Yu, Jianbo Shi
  • Mathematics, Computer Science
  • Proceedings Ninth IEEE International Conference…
  • 13 October 2003
TLDR
This work proposes a principled account on multiclass spectral clustering by solving a relaxed continuous optimization problem by eigen-decomposition and clarifying the role of eigenvectors as a generator of all optimal solutions through orthonormal transforms. Expand
The CMU Motion of Body (MoBo) Database
TLDR
The capture setup, the collection procedure and the organization of the database are described, which contains 25 individuals walking on a treadmill in the CMU 3D room. Expand
Spectral segmentation with multiscale graph decomposition
TLDR
The segmentation algorithm works simultaneously across the graph scales, with an inter-scale constraint to ensure communication and consistency between the segmentations at each scale, and incorporates long-range connections with linear-time complexity, providing high-quality segmentations efficiently. Expand
Contour and Texture Analysis for Image Segmentation
TLDR
This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent brightness and texture, and introduces a gating operator based on the texturedness of the neighborhood at a pixel to facilitate cue combination. Expand
Balanced Graph Matching
TLDR
A new spectral relaxation technique for approximate solutions to matching problems, that naturally incorporates one-to-one or one- to-many constraints within the relaxation scheme is given. Expand
A Random Walks View of Spectral Segmentation
TLDR
It is proved that the Normalized Cut method arises naturally from the framework and a complete characterization of the cases when the Normalization Cut algorithm is exact is provided. Expand
Learning Segmentation by Random Walks
TLDR
This interpretation shows that spectral methods for clustering and segmentation have a probabilistic foundation and proves that the Normalized Cut method arises naturally from the framework. Expand
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