
Night Vision Study
Description
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Content
- Cover
- Table of Contents
- Introduction
- CHAPTER 1: Threshold Visibility Levels for the Adrian Visibility Model under Nighttime Driving Conditions
- Introduction
- Methods
- Data/Model Integration
- Analysis
- Results
- Discussion
- Conclusion
- References
- CHAPTER 2: Validation of Digital Image Representations of Low-Illumination Scenes
- Introduction
- Low-Illumination Photography Methods
- Methods
- Overview
- Scene SetUp
- Camera
- Images
- Contrast Charts
- Displays and Printer
- Calibrating the Display Devices
- Image Processing
- Image Size and Viewing Distance
- Subjects
- Experimental Procedure
- Print format
- Computer Monitor/Projector
- Ratings
- Results
- Print Photographs
- CRT-Displayed Photographs
- Projector-Displayed Photographs
- CRT vs. Projector
- Discussion
- Conclusion
- References
- CHAPTER 3: Digital Camera Calibration for Luminance Estimation in Nighttime Visibility Studies
- Introduction
- Background
- Opto-Electronic Conversion Function
- Color
- Noise
- Methods
- Equipment
- Software
- Scenes
- Processing
- Color Filter Array
- Lights, Flats, Darks, and Offsets
- Work Flow
- Results
- Discussion
- Conclusion
- Acknowledgments
- References
- Definitions, Acronyms, Abbreviations
- CHAPTER 4: Simulating Headlamp Illumination Using Photometric Light Clusters
- Introduction
- Background on Light Simulation
- Simulated Light Photometrics
- Creating a Photometric Light Cluster
- Analyze Light Distribution
- Project Quadrants at Distances
- Converting Photo Plates to Mesh Objects
- Determine Computer-Generated Light Source Locations
- Create Projection Maps for Computer-Generated Light Sources
- Validation
- Discussion and Conclusions
- References
- CHAPTER 5: Validation of High Dynamic Range Photography as a Tool to Accurately Represent Low-Illumination Scenes
- Introduction
- Methods
- Participants
- Test Scene
- Digital Photographs
- Procedure
- Analysis
- Results
- Discussion
- Conclusion
- References
- CHAPTER 6: Nighttime Videographic Projection Mapping to Generate Photo-realistic Simulation Environments
- Introduction
- Background
- Baseline Video Footage Used for Comparison
- Testing the Methodology
- a. Video Footage of Driving Environment
- b. Geometry Data of the Driving Environment
- c. Video Footage of Vehicles in Varying Conditions
- d. Geometry Data of the Vehicles
- e. Projection Mapping for a Computer Environment
- f. Computer Visualization of Vehicles
- g. Combining Environment and Vehicle Systems Together
- h. Varying Parameters of Vehicle and Scene
- Additional Scenarios
- Conclusion
- References
- About the Author
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