You are previewing Innovative Research in Attention Modeling and Computer Vision Applications.
O'Reilly logo
Innovative Research in Attention Modeling and Computer Vision Applications

Book Description

Robotics and autonomous systems can aid disabled individuals in daily living or make a workplace more productive, but these tools are only as effective as the technology behind them. Robotic systems must be able to accurately identify and act upon elements in their environment to be effective in performing their duties. Innovative Research in Attention Modeling and Computer Vision Applications explores the latest research in image processing and pattern recognition for use in robotic real-time cryptography and surveillance applications. This book provides researchers, students, academicians, software designers, and application developers with next-generation insight into the use of computer vision technologies in a variety of industries and endeavors. This premier reference work includes chapters on topics ranging from biometric and facial recognition technologies, to digital image and video watermarking, among many others.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Preface
  6. Section 1: Visual Attention Modeling and Applications
    1. Chapter 1: 2D and 3D Visual Attention for Computer Vision
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. VISUAL ATTENTION
      4. 2. VISUAL ATTENTION AND THE HUMAN VISUAL SYSTEM
      5. 3. EYE MOVEMENTS AND EYE-TRACKING
      6. 4. COMPUTATIONAL MODELING OF VISUAL ATTENTION
      7. 5. EXTENSION TO THE COMPUTATIONAL MODELING OF STEREOSCOPIC 3D VISUAL ATTENTION
      8. 6. CONCLUSION
      9. REFERENCES
    2. Chapter 2: Applications of Visual Attention in Image Processing, Computer Vision, and Graphics
      1. ABSTRACT
      2. INTRODUCTION
      3. COMPUTATIONAL MODELS OF VISUAL ATTENTION
      4. APPLICATIONS IN IMAGE AND VIDEO PROCESSING
      5. APPLICATIONS IN COMPUTER VISION
      6. ROBOTICS
      7. APPLICATIONS IN COMPUTER GRAPHICS
      8. CONCLUSION
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    3. Chapter 3: Biologically-Inspired Models for Attentive Robot Vision
      1. ABSTRACT
      2. INTRODUCTION
      3. PRIMATE VISUAL SYSTEM
      4. VISUAL ATTENTION
      5. CLASSIFICATION OF BIOLOGICALLY-INSPIRED MODELS FOR ATTENTIVE ROBOT VISION
      6. SIMPLE SALIENCY-BASED MODELS
      7. PROTO-OBJECT-BASED MODELS
      8. ITERATIVE MODEL
      9. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
      10. ACKNOWLEDGMENT
      11. REFERENCES
      12. ADDITIONAL READING
    4. Chapter 4: Visual Attention Guided Object Detection and Tracking
      1. ABSTRACT
      2. INTRODUCTION
      3. A BRIEF REVIEW ON EXISTING TECHNIQUES
      4. VISUAL ATTENTION IN OBJECT TRACKING
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
      10. ENDNOTE
    5. Chapter 5: Content-Aware Image Retargeting
      1. ABSTRACT
      2. INTRODUCTION
      3. ESTIMATING IMPORTANCE
      4. RETARGETING APPROACHES
      5. EVALUATION STRATEGIES FOR RETARGETING APPROACHES
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    6. Chapter 6: Video Saliency Detection for Visual Cryptography-Based Watermarking
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. VISUAL CRYPTOGRAPHY IN WATERMARKING
      4. 3. EXISTING VC BASED VIDEO WATERMARKING TECHNIQUES
      5. 4. IMPORTANCE OF VIDEO SALIENCY DETECTION IN WATERMARKING
      6. 5. PROPOSED VC BASED VIDEO WATERMARKING APPROACH USING MOTION VECTORS AS SALIENT FEATURES
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    7. Chapter 7: Study of Loss of Alertness and Driver Fatigue Using Visibility Graph Synchronization
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
  7. Section 2: Other Computer Vision Applications
    1. Chapter 8: A Generic Design for Implementing Intersection between Triangles in Computer Vision and Spatial Reasoning
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. USING VECTORS TO SOLVE EQUATIONS AND PITFALLS
      5. USING VECTORS TO REPRESENT TRIANGLES
      6. SOLVING INEQUALITIES AND PITFALLS
      7. THE CONVENTIONAL TRIANGLE-TRIANGLE INTERSECTION STRATEGIES
      8. CATEGORIZING OF TRIANGLE-TRIANGLE INTERSECTION
      9. EXAMPLE FIGURES FOR INTERSECTION BETWEEN A PAIR OF TRIANGLES
      10. SPECIALIZED INTERSECTION METHODS AND ALGORITHMS
      11. THE TRIANGLE-TRIANGLE INTERSECTION ALGORITHMS
      12. GENERIC ALGORITHM FOR TRIANGLE-TRIANGLE INTERSECTION
      13. EXPERIMENTAL RESULTS
      14. APPLICATIONS OF TRIANGLE-TRIANGLE INTERSECTION
      15. CONCLUSION
      16. REFERENCES
    2. Chapter 9: Multiple Object Tracking by Scale Space Representation of Objects, Method of Linear Assignment, and Kalman Filter
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
    3. Chapter 10: Digital Forensics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. DIGITAL CONTENT PROTECTION AND DIGITAL FORENSICS
      4. 3. DIGITAL IMAGE FORGERY AND FORENSICS
      5. 4. IMAGE SOURCE IDENTIFICATION
      6. 5. CONCLUSION AND FUTURE WORK
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    4. Chapter 11: Passive Video Tampering Detection Using Noise Features
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. VIDEO TAMPERING
      5. CAMERA PIPELINE PROCESSING
      6. NOISE FEATURES EXTRACTION TECHNIQUES
      7. IMPORTANCE OF NOISE FEATURES
      8. VIDEO TAMPERING DETECTION METHOD USING NOISE FEATURES
      9. RECOMMENDATION
      10. VIDEO SOURCE IDENTIFICATION USING NOISE FEATURES
      11. ISSUE AND CHALLENGES IN VIDEO TAMPERING DETECTION
      12. APPLICATION
      13. CONCLUSION AND FUTURE DIRECTION
      14. REFERENCES
      15. ADDITIONAL READING
      16. KEY TERMS AND DEFINITION
    5. Chapter 12: A Survey on Palmprint-Based Biometric Recognition System
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PALMPRINT ACQUISITION AND PREPROCESSING
      5. FEATURE EXTRACTION AND MATCHING
      6. FUSION
      7. IDENTIFICATION IN LARGE DATABASES
      8. CONCLUSION
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    6. Chapter 13: Emotion Recognition Using Facial Expression
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. FACE EXPRESSION: ISSUES AND CHALLENGES
      5. 4. DATABASE PREPARATION AND DESCRIPTION
      6. 5. PROPOSED METHODOLOGY
      7. 6. EXPERIMENTATION RESULTS AND DISCUSSION
      8. 7. CONCLUSION
      9. 8. FUTURE DIRECTION
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
    7. Chapter 14: Facial Expression Analysis Using 3D Range Images
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. FUTURE DIRECTIONS OF WORK
      6. CONCLUSION
      7. ACKNOWLEDGMENT
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    8. Chapter 15: Scalable Video Watermarking
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. DIGITAL VIDEO WATERMARKING
      4. 2. SCALABLE VIDEO
      5. 3. SCALABLE IMAGE WATERMARKING
      6. 4. SCALABLE VIDEO WATERMARKING
      7. REFERENCES
    9. Chapter 16: Digital Image Watermarking Based on Fractal Image Coding
      1. ABSTRACT
      2. INTRODUCTION
      3. DIGITAL WATERMARKING TECHNIQUES
      4. PROPOSED WATERMARKING TECHNIQUE
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
  8. Compilation of References
  9. About the Contributors