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Mobile Computational Photography
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Classroom Contents
Tools for Mobile Photography and Computer Vision
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- 1 Intro
- 2 NVIDIA Mobile Computer Vision
- 3 Computer Vision = New Applications
- 4 Computer Vision = Vehicle Safety
- 5 Mobile Computing on a Tear
- 6 Tegra 2 - Heterogeneous Multi-core
- 7 ARM is Pervasive and Open
- 8 TEGRA ROADMAP
- 9 OpenCV Functionality Overview Image processing
- 10 OpenCV for CUDA
- 11 Current OpenCV Cuda Functionality
- 12 OpenCV for Android
- 13 Tegra Android Development Pack
- 14 Android Apps Java Applications
- 15 OpenCV supports Java and Native
- 16 OpenCV Java API Example
- 17 The Embedded Vision Alliance
- 18 Computer Vision vs. Photography
- 19 Some computational photography apps
- 20 Mobile Computational Photography
- 21 MCP Problem 1: Lack of control & accesso
- 22 MCP Problem 2: Wrong model
- 23 The FCam Architecture
- 24 Sensor
- 25 Image Signal Processor (ISP)
- 26 Devices
- 27 Implementations
- 28 Tegra developer board
- 29 FCam: Open Source Project
- 30 Exposure metering examples
- 31 Auto White Balance
- 32 Estimating the color temperature
- 33 Contrast-based Passive Autofocus
- 34 Exposure Fusion: Simplified HDR
- 35 Implemented on N900
- 36 Lucky Imaging: Hand-held long exposures
- 37 First assignment: Autofocus - 1 week
- 38 Remote flash over Bluetooth
- 39 Interactive Photomontage
- 40 Kal-El Reference Design
- 41 FCam on Tegra: Baby steps
