Part III
Applications of Attention Selection Models
Part III: Applications of Attention Selection Models
by Weisi Lin, Liming Zhang
Selective Visual Attention: Computational Models and Applications
- Cover
- Title Page
- Copyright
- Preface
- Part I: Basic Concepts and Theory
- Part II: Computational Attention Models
- Chapter 3: Computational Models in the Spatial Domain
- 3.1 Baseline Saliency Model for Images
- 3.2 Modelling for Videos
- 3.3 Variations and More Details of BS Model
- 3.4 Graph-based Visual Saliency
- 3.5 Attention Modelling Based on Information Maximizing
- 3.6 Discriminant Saliency Based on Centre–Surround
- 3.7 Saliency Using More Comprehensive Statistics
- 3.8 Saliency Based on Bayesian Surprise
- 3.9 Summary
- References
- Chapter 4: Fast Bottom-up Computational Models in the Spectral Domain
- 4.1 Frequency Spectrum of Images
- 4.2 Spectral Residual Approach
- 4.3 Phase Fourier Transform Approach
- 4.4 Phase Spectrum of the Quaternion Fourier Transform Approach
- 4.5 Pulsed Discrete Cosine Transform Approach
- 4.6 Divisive Normalization Model in the Frequency Domain
- 4.7 Amplitude Spectrum of Quaternion Fourier Transform (AQFT) Approach
- 4.8 Modelling from a Bit-stream
- 4.9 Further Discussions of Frequency Domain Approach
- References
- Chapter 5: Computational Models for Top-down Visual Attention
- 5.1 Attention of Population-based Inference
- 5.2 Hierarchical Object Search with Top-down Instructions
- 5.3 Computational Model under Top-down Influence
- 5.4 Attention with Memory of Learning and Amnesic Function
- 5.5 Top-down Computation in the Visual Attention System: VOCUS
- 5.6 Hybrid Model of Bottom-up Saliency with Top-down Attention Process
- 5.7 Top-down Modelling in the Bayesian Framework
- 5.8 Summary
- References
- Chapter 6: Validation and Evaluation for Visual Attention Models
- Chapter 3: Computational Models in the Spatial Domain
- Part III: Applications of Attention Selection Models
- Part IV: Summary
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