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Schedule

Schedule. F5: Texture and segmentation F6: Energy and graph based segmentation F7: Active contours, snakes and level sets F8: Fitting, Hough transform F9: Recognition and classification …. A Vision Application. Binary Image Segmentation. How ?. Cost function.

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Schedule

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  1. Schedule • F5: Texture and segmentation • F6: Energy and graph based segmentation • F7: Active contours, snakes and level sets • F8: Fitting, Hough transform • F9: Recognition and classification • …

  2. A Vision Application Binary Image Segmentation How ? Cost function Models our knowledge about natural images Optimize cost function to obtain the segmentation

  3. Why do these tokens belong together?

  4. TRAFFIC RESEARCH • Increase traffic safety • Increase traffic flow • Together with Traffic Dept in Lund. • Automatic detection and analysis of objects and events in traffic environment

  5. Image Clusters on intensity Clusters on color K-means clustering using intensity alone and color alone

  6. Image Clusters on color K-means using color alone, 11 segments

  7. K-means using color alone, 11 segments.

  8. K-means using colour and position, 20 segments

  9. Represent tokens using a weighted graph. affinity matrix Cut up this graph to get subgraphs with strong interior links Graph theoretic clustering

  10. Example eigenvector points eigenvector matrix

  11. More than two segments • Two options • Recursively split each side to get a tree, continuing till the eigenvalues are too small • Use the other eigenvectors

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