Applied Computer Vision (3-0-0)
Course Contents:

Introduction & Overview; Image formation concepts; Camera models & Optics; Camera Parameters; Camera calibration (Epipolar geometry); Fundamental & Essential Matrix; Noise Estimation & Removal; Feature extraction overview; Feature detection; 3D sensing; Surface reconstruction; Active Vision/control; Vision & learning.

Class Timing
To be announced

Prerequisite: None.

Course Details

Evaluation Process

Related Papers

List of Students

Lectures

Class Test 1 Question Paper

Mid-Sem Exam Question Paper

End-Sem Exam Question Paper

Attendance

Marks