116H59C501
Advanced Computer Vision
Introduction to Computer Vision
1.1 Overview of Computer Vision, Document Image, Biometrics, Object Recognition, Tracking, Medical Image Analysis, Content-Based Image Retrieval, Video Data Processing
Image Formation Models
2.1 Orthographic & Perspective Projection, Camera model and Camera calibration, Binocular imaging systems, Multiple views geometry
2.2 Structure determination, shape from shading , Photometric Stereo, Depth from Defocus , Construction of 3D model from images
2.3 Feature Extraction, Image preprocessing, Image representations (continuous and discrete), Edge detection
Motion Estimation
3.1 Regularization theory, Optical computation, Stereo Vision, Motion estimation, Structure from motion, Kalman Filter, SURF, SIFT
3.2 Contour based representation, Region based representation, Deformable curves and surfaces, Snakes and active contours, Level set representations, Fourier and wavelet descriptors, Multiresolution analysis
Object recognition and Image Understanding
4.1 Hough transforms and other simple object recognition methods, Shape correspondence and shape matching, Principal component analysis, Shape priors for recognition, Pattern recognition methods, HMM, GMM and EM
Applications
5.1 Surveillance – foreground-background separation – particle filters – Chamfer matching, tracking, and occlusion – combining views from multiple cameras
5.2 Photo album – Face detection – Face recognition – Eigen faces – Active appearance and 3D shape models of faces Application.
5.3 Human gait analysis Application: In-vehicle vision system: locating roadway – road markings – identifying road signs – locating pedestrians
1.1 Overview of Computer Vision, Document Image, Biometrics, Object Recognition, Tracking, Medical Image Analysis, Content-Based Image Retrieval, Video Data Processing
Image Formation Models
2.1 Orthographic & Perspective Projection, Camera model and Camera calibration, Binocular imaging systems, Multiple views geometry
2.2 Structure determination, shape from shading , Photometric Stereo, Depth from Defocus , Construction of 3D model from images
2.3 Feature Extraction, Image preprocessing, Image representations (continuous and discrete), Edge detection
Motion Estimation
3.1 Regularization theory, Optical computation, Stereo Vision, Motion estimation, Structure from motion, Kalman Filter, SURF, SIFT
3.2 Contour based representation, Region based representation, Deformable curves and surfaces, Snakes and active contours, Level set representations, Fourier and wavelet descriptors, Multiresolution analysis
Object recognition and Image Understanding
4.1 Hough transforms and other simple object recognition methods, Shape correspondence and shape matching, Principal component analysis, Shape priors for recognition, Pattern recognition methods, HMM, GMM and EM
Applications
5.1 Surveillance – foreground-background separation – particle filters – Chamfer matching, tracking, and occlusion – combining views from multiple cameras
5.2 Photo album – Face detection – Face recognition – Eigen faces – Active appearance and 3D shape models of faces Application.
5.3 Human gait analysis Application: In-vehicle vision system: locating roadway – road markings – identifying road signs – locating pedestrians