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Supporting Landmark Image Retrieval with Skyline Extraction Techniques

Supporting Landmark Image Retrieval with Skyline Extraction Techniques . Date : 2012 / 04 / 12 資訊碩一 10077034 蔡勇儀 @ LAB603 . Outline. Introduction Preliminaries Method Experimental result Conclusions. Introduction. Image retrieval have more challenge than text retrieval.

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Supporting Landmark Image Retrieval with Skyline Extraction Techniques

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  1. Supporting Landmark Image Retrieval with Skyline Extraction Techniques Date :2012 / 04/ 12 資訊碩一 10077034 蔡勇儀 @LAB603

  2. Outline • Introduction • Preliminaries • Method • Experimental result • Conclusions

  3. Introduction • Image retrieval have more challenge than text retrieval. • Use low-level feature to identify objects is non-trivial. • Skyline is a good feature to identify landmark contour.

  4. Outline • Introduction • Preliminaries • Method • Experimental result • Conclusions

  5. Traditional image retrieval • Traditional techniques for image retrieval rely on some metadata (i.e., keywords or captions of image) • It isn’t a good method for practical applications since it is labor intensive and need more space.

  6. Content-based image retrieval • Content-based image retrieval(CBIR) is using image’s feature for retrieval. • Query-by-example • Query-by-sketch • Relevance feedback technique

  7. Identifying landmarks with skylines • Region-growing-based • Using same color region extend find the skylines • Weak robustness on the sky with cloud or complex background • Edge-based • Edge detection • Retaining the points which are luminous intensity change sharply • Using other method to find clear skyline.

  8. Outline • Introduction • Preliminaries • Method • Experimental result • Conclusions

  9. Method(1/4) - Difficulties • Small portion of edge points constitute the proper skyline. • Skyline may not fully-connected. • Steep or tortuous.

  10. Method(2/4) - RON • RON(radius of neighborhood) • Defining the search region (ex. RON = 2 -> grid zone = 5*5) • Solving the difficulties.

  11. Method(3/4) – Direction priority • Using clockwise • Good direction for traversal skyline.

  12. Method(4/4) – Find the skyline • Using Sobel Filter for edge detection • Using DFS for search. (Need decide the start point?)

  13. Outline • Introduction • Preliminaries • Method • Experimental result • Conclusions

  14. Experimental Result • DP VS This method ( O(n2) & O(n) )

  15. Outline • Introduction • Preliminaries • Method • Experimental result • Conclusions

  16. Conclusions • This is a feasible for landmark image retrieval. • If there are more line cross the image? • If sky have complex object(ex. Light or cloud…)? • If the beginning point is not in skyline? • More problem need to solving…

  17. Thank for your listening! • Q&A

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