計算攝影學

Digital imaging represents one of the most precise and highest bandwidth forms of sensing available today. The adoption of digital imaging is further encouraged by increasingly more powerful image processing techniques (collectively known as “Computational Photography”). As examples, drones, self-driving car, social media face-recognition, food and package industry etc. all rely on machine vision/imaging as their primary form of sensor. This class prepares students for a future research and engineering career that is inevitably tied to computational photography. Course objectives: • Knowledge of digital camera and lens. • Common image-processing techniques. • Calibration techniques for technical imaging (color, size, 3D calibration etc.). • Examples of unconventional computational photography techniques. • Applications: 3D measurement, machine vision, drone-imaging etc. TL,DR: "How to use camera to measure things scientifically."

• 工程數學 • Matlab/Python coding or equivalent. • We'll use smartphone to take a lot of raw data. • Course lecture and assignment in English.

1.5-2hr lecture per week. Followed by ~1hr project work, demo and Q&A time. Classes will strive to be interactive, and adjusted around a few core topics based on evolving students needs and interests.

20% each across 5 hands-on, mini-projects. No exam.

• Basic Image Processing
• Camera and Lens
• Calibration
• Application: 3D measurement
• Advanced: Light-Field Imaging
• Application: machine vision

None. (All materials will be provided).

聯絡方式

tanzu@nctu.edu.tw