AIMS AND CONTENT

LEARNING OUTCOMES

This course presents the fundamentals in computer vision. Topics include camera modelling, camera calibration, image processing, pose estimation, multi view geometry, visual tracking, and vision based calibration.

TEACHING METHODS

• theoretical classes followe by practical (step-by-step) labs

SYLLABUS/CONTENT

Introduction to computer vision for robotics applications

Part 1 - image processing fundamentals

• Digital image fundamentals: sensing and acquisition, sampling and quantization, basic operations
• Intensity transformations and spatial filtering (filtering in the frequency domain) 
• Edge and corner detection
• Color image processing
• Hough transforms and image segmentation
• Early vision: feature detection and regularization. Optimal filters and multichannel representations (Gabor functions)

Part 2 - motion analysis and navigation

• Motion: 3D and 2D motion fields, dense and sparse optical flow. Dominant motion estimation                              
• Tracking with linear dynamic models (Kalman Filter)
• Autonomous navigation

Part 3 - geometry

• 3D computer vision fundamentals
• The geometry of image formation: review of projective geometry (basic), projective transformations, camera models and single view geometry, camera calibration
• Stereopsis: epipolar geometry, stereo rectification, depth estimation, 3D reconstruction 

​Conclusions: image matching and  image retrieval;  introduction to object and action recognition methods in HRI

RECOMMENDED READING/BIBLIOGRAPHY

Recommended texts:

• R.C. Gonzalez and R.E. Woods, Digital image processing, Prentice-Hall, 2008.
• E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall,  1998.

Further readings: Material distributed by lecturers 

TEACHERS AND EXAM BOARD

Exam Board

FRANCESCA ODONE (President)

FABIO SOLARI (President)

RENATO UGO RAFFAELE ZACCARIA (President)

MANUELA CHESSA

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

• 30% continuous assessment  through practical laboratory exercises done throughout the semester,
• 70% from end-semester exam.The final exam consists in a two-hour written examination. It is not allowed to consult books, notes, or other written material. 

Exam schedule