Image processing and computer vision Chapter 4: Feature extraction and tracking features vo. a
Image processing and computer vision Chapter 4: Feature extraction and tracking features v0.a 1
Intro. Edge features Region features Corner features tracking by correlation You will learn Edge features Region features Corner features Tracking of corner features features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation You will learn • Edge features • Region features • Corner features • Tracking of corner features features v0.a 2
Intro. Edge features Region features Corner features tracking by correlation Different types of features Edges Edge detection ° Regions region growing Corner features Corner feature detection and tracking Stereo correspondence features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Different types of features • Edges – Edge detection • Regions – region growing • Corner features – Corner feature detection and Tracking – Stereo correspondence features v0.a 3
Intro. Edge features Region features Corner features tracking by correlation Edge detection Tools: Use matlab edge detectors: edge. m g. Template based Sobel features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Edge detection • Tools: Use MATLAB edge detectors: edge.m • E.g. Template based: Sobel features v0.a 4
Intro. Edge features Region features Corner features tracking by correlation Example by matlab from demo of Image processing toolbox: edge.m Edge Detection Demo Eile Edit View Insert Tools Window Help Original Blood Image Edge Map Threshold . Automatic Edge Detection Method Info Sobel Direction: Both Close Press Apply to compute edges features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Example by Matlab from demo of Image processing toolbox: edge.m features v0.a 5
Intro. Edge features Region features Corner features tracking by correlation Region growing Boundary detection Snake- an energy minimization method for finding boundary http://www.markschulze.net/snakes/ use mouse to select object press any key to start operation features vo. a 6
Intro. | Edge features | Region features | Corner features | tracking by correlation Region growing • Boundary detection • Snake – an energy minimization method for finding boundary – http://www.markschulze.net/snakes/ • use mouse to select object, • press any key to start operation features v0.a 6
Intro. Edge features Region features Corner features tracking by correlation Region growing image processing toolbox detecting object demo Source image Output regions features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Region growing image processing toolbox • detecting object demo features v0.a 7 • Source image Output regions
Intro. Edge features Region features Corner features tracking by correlation Corner features The correspondence problem and feature tracking problem Applications For 2 stereo images, identify Cyklt-shows-feats. m features 2D features corresponding to the same 3D feature For a sequence of images in a movie identify 2D features corresponding to the same 100 3D feature Demo http://ww.youtube.com/watch ?V=RXpX9TJIpdo features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Corner features The correspondence problem and feature tracking problem • Applications – For 2 stereo images, identify 2D features corresponding to the same 3D feature . – For a sequence of images in a movie, identify 2D features corresponding to the same 3D feature . features v0.a 8 Demo: http://www.youtube.com/watch ?v=RXpX9TJlpd0
Intro. Edge features Region features Corner features tracking by correlation Camera moved, find correspondences for Neighborhood a neighboring images Image at t=to Image at tto fat or left image features vo. a (or right image) 9
Intro. | Edge features | Region features | Corner features | tracking by correlation Camera moved, find correspondences for neighboring images features v0.a 9 • Image at t=t0 (or left image) Image at t=t0+dt (or right image) Neighborhood A
Intro. Edge features Region features Corner features tracking by correlation dea of a corner feature This is a corner feature, why? The idea is to find pixels with high gradient at orthogonal directions Example 国 This is not a corner feature, why? features vo. a
Intro. | Edge features | Region features | Corner features | tracking by correlation Idea of a corner feature • The idea is to find pixels with high gradient at orthogonal directions • Example • features v0.a 10 This is a corner feature, why? This is not a corner feature, why? ?