
Video Processing and Computational Video
Description
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With the swift development of video imaging technology and the drastic improvements in CPU speed and memory, both video processing and computational video are becoming more and more popular. Similar to the digital revolution in photography of fifteen years ago, today digital methods are revolutionizing the way television and movies are being made. With the advent of professional digital movie cameras, digital projector technology for movie theaters, and 3D movies, the movie and
television production pipeline is turning all-digital, opening up
numerous new opportunities for the way dynamic scenes are acquired, video footage can be edited, and visual media may be experienced.
This state-of-the-art survey provides a compilation of selected articles resulting from a workshop on Video Processing and Computational Video, held at Dagstuhl Castle, Germany, in October 2010. The seminar brought together junior and senior
researchers from computer vision, computer graphics, and image communication, both from academia and industry, to address the challenges in computational video. During this workshop, 43 researchers from all over the world discussed the state of the art, contemporary challenges, and future research in imaging,
processing, analyzing, modeling, and rendering of real-world, dynamic scenes.
The 8 thoroughly revised papers presented were carefully reviewed and selected from more than 30 lectures given at the seminar. The articles give a good overview of the field of computational video and video processing with a special
focus on computational photography, video-based rendering, and 3D video.
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Content
- Intro
- Title
- Preface
- Table of Contents
- Video Processing and Computational Video
- Towards Plenoptic Raumzeit Reconstruction
- Introduction
- Related Work
- Floating Textures
- Soft Visibility
- GPU Implementation
- View and Time Interpolation in Image Space
- Image Morphing and Spatial Transformations
- Image Deformation Model for Time and View Interpolation
- Optimizing the Image Deformation Model
- Rendering
- Plenoptic Raumzeit Reconstruction
- Overview
- Image Selection and Processing Order
- Initialization
- Expansion Phase
- Patch Optimization
- Filtering
- Discussion and Conclusion
- Two Algorithms for Motion Estimation from Alternate Exposure Images
- Introduction
- Related Work
- Image Formation Model
- Least Squares Approach
- Additional Assumptions
- Pointwise Optimization Problem
- Occlusion Detection
- Parameter Sensitivity
- Total Variation Approach
- Additional Assumptions
- Global Optimization Problem
- TV-L1 Minimization
- Implementation
- Comparison of Different Motion Estimation Algorithms
- Motion Fields for Synthetic Test Scenes
- Frame Interpolation for Synthetic Test Scenes
- Real-World Recordings
- Discussion
- Comparison of the Two Alternate Exposure Approaches
- Limitations and Advantages from Alternate Exposure Imaging in Image Based Motion Estimation
- Conclusion
- Understanding What We Cannot See: Automatic Analysis of 4D Digital In-Line Holographic Microscopy Data
- Introduction
- Detection of 3D Positions
- Digital In-Line Holographic Microscopy (DIHM)
- Detection of the Microorganisms
- Automatic Extraction of 3D Trajectories
- Cost Function and Bipartite Graph Matching
- Multi-level Hungarian for Missing Data
- The Final Hungarian
- Motion Pattern Classification
- Hidden Markov Models
- Types of Patterns
- Features Used for Classification
- Building and Training the HMMs
- Experimental Results
- Performance of the Standard Hungarian
- Performance of the Multi-level Hungarian
- Performance of the Complete Algorithm
- Evaluation of the Features Used for Classification
- Classification on Other Sequences
- Conclusions
- 3D Reconstruction and Video-Based Rendering of Casually Captured Videos
- Introduction
- Related Work
- Offline Processing
- Static Elements Reconstruction
- Spatial, Temporal and Photometric Calibration
- Dynamic Elements Reconstruction
- Reconstruction Using Temporal Information.
- Reconstruction Using Spatial Information.
- Comparison.
- Online Navigation
- User-Interface
- Video-Based Rendering
- Volumetric Representation.
- Billboard Representation and Transition Optimization.
- Rendering the Virtual Camera.
- Experiments
- Conclusions
- Silhouette-Based Variational Methods for Single View Reconstruction
- Introduction
- Single View Reconstruction
- Issues and Related Work
- Contribution
- Reconstruction Workflow
- Implicit Variational Surfaces
- Inflation via Shape Prior
- Optimization via Convex Relaxation
- Experiments
- Inflation via Volume Prior
- Optimization via Convex Relaxation
- Optimality Bounds
- Theoretical Analysis of Material Concentration
- Experiments
- Comparison
- Conclusion
- Single Image Blind Deconvolution with Higher-Order Texture Statistics
- Introduction
- Prior Work
- Single Image Blind Deconvolution
- Image Model
- Sharp Image Prior
- Blur Scale Prior
- Blur Scale Identification and Image Deblurring
- Learning Procedure and Blur Scale Identification
- Image Deblurring
- A Geometric Viewpoint on Blur Scale Identification
- Coded Aperture Selection
- Experiments
- Performance Comparison
- Results on Real Data
- Computational Cost
- Conclusions
- Compressive Rendering of Multidimensional Scenes
- Introduction
- Previous Work
- Transform Compression in Rendering
- Accelerating Ray Tracing and Rendering
- Reconstruction of Missing Data
- Compressed Sensing and Computer Graphics
- Compressed Sensing Theory
- Theoretical Background
- Overview of ROMP Algorithm
- Overview of SpaRSA Algorithm
- Restricted Isometry Condition (RIC)
- Algorithm Overview
- Example of 1D Signal Reconstruction
- Application to 2D Signals - Image Reconstruction
- Timing Performance
- Image Quality
- Application to 2D Signals - Antialiasing
- Application to 3D Signals - Motion Blur
- Application to 3D Signals - Video
- Application to 4D Signals - Depth of Field
- Application to 4D Signals - Area Light Source
- Discussion
- Conclusion
- Efficient Rendering of Light Field Images
- Introduction
- Prior Work
- System Overview
- Building the Geometric Model
- Determine the Best Viewpoints
- Assembling of the Light Field
- Rendering
- Efficient Ray Cast Implementation
- Multi-threaded Implementation on the Central Processing Unit
- Implementation on the Graphics Hardware
- Results
- Best Next View Selection
- Interpolation Results
- Runtime
- Conclusion
- Author Index
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