Searching for authors named "Kun Huang" – sorted by Relevance.
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Hierarchical and Integrated Algorithms: Comparison and Applications in . . .
- In this paper, we study several issues in motion estimation and object recognition. First, we compare the performance of two hierarchical and integrated methods in motion estimation. Second, we address the use of a simulated annealing algorithm for object recognition. This algorithm is then adapted
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A Unifying Theorem for Spectral Embedding and Clustering
- A unifying theorem for spectral embedding and clustering Matthev Brand and Kun Huang Mitsubishi
- Cited by 31 (0 self) – Add To MetaCart
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Generalized Rank Conditions in Multiple View Geometry with Applications to Dynamical Scenes
- Generalized Rank Conditions in Multiple View Geometry with Applications to Dynamical Scenes ? Kun
- Cited by 4 (3 self) – Add To MetaCart
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Symmetry-based photo editing
- Symmetry-Based Photo Editing Kun Huang Wei Hong Yi Ma Department of Electrical and Computer
- Cited by 2 (1 self) – Add To MetaCart
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A multi-scale hybrid linear model for lossy image representation
- A Multi-Scale Hybrid Linear Model for Lossy Image Representation ∗ Wei Hong † John Wright † Kun
- Cited by 6 (1 self) – Add To MetaCart
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Rank Deficiency Condition of the Multiple View Matrix for Mixed Point and Line Features
- Matrix for Mixed Point and Line Features Yi Ma, Jana Kosecka and Kun Huang Abstract| Geometric
- Cited by 5 (3 self) – Add To MetaCart
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A unifying theorem for spectral embedding
- embedding and clustering Matthew Brand and Kun Huang TR2002-42 January 2003 Abstract Spectral methods use
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Minimum Effective Dimension for Mixtures of Subspaces: a Robust GPCA Algorithm
- Applications Kun Huang and Yi Ma René Vidal Dept. of Electrical & Computer Engineering Dept. of Biomedical
- Cited by 8 (2 self) – Add To MetaCart
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Sparse representation of images with hybrid linear models
- SPARSE REPRESENTATION OF IMAGES WITH HYBRID LINEAR MODELS Kun Huang Allen Y. Yang Yi Ma
- Cited by 1 (0 self) – Add To MetaCart
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Rank Conditions on the Multiple View Matrix
- Rank Conditions on the Multiple View Matrix Yi Ma and Kun Huang Electrical & Computer
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