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教你輕鬆寫 Hw2

教你輕鬆寫 Hw2. Find KEYPOINTS. (1) 經過 SIFT ， keypoints 資訊存在 descriptor 裡 (2)Descriptor 存有 128 維度的資料 (2) 利用 object img 與 target img 的 descriptor 資訊去找建立 K-NN. How to RaNSAC. 對 object img 每個 keypoint 找到 K-NN Ex. 使用 3-NN. 可以看出，組合的方式有很多種 1->1 1->7 2->4 2->11 … 3->3 3->6 4->7 4->7.

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教你輕鬆寫 Hw2

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  1. 教你輕鬆寫Hw2

  2. Find KEYPOINTS (1)經過SIFT，keypoints資訊存在descriptor裡 (2)Descriptor存有128維度的資料 (2)利用object img與target img的descriptor資訊去找建立K-NN

  3. How to RaNSAC 對object img每個keypoint找到K-NN Ex. 使用3-NN 可以看出，組合的方式有很多種 1->1 1->7 2->4 2->11 … 3->3 3->6 4->7 4->7

  4. How to RaNSAC • 以下提供一種作法(非一定)(以4-NN為例)： • (1)設定總共要跑幾個round: z，不同的round會挑不同4個objkeypoint • (2)在每個round有四個random number:n1,n2,n3,n4 • 分別代表四個objkeypoints的index • (3)分別存取四個objkeypoints的nearest neighbors(共4*4*4*4種可能) • (4)每次都要算Homography matrix，並計算inlier數

  5. Homography matrix (1)考慮找出的homography matrix的正確性(例如.inlier數量最多最正確) (2)將objimg的coordinate乘上該matrix (3)Warping到target img上面，並且框出邊框

  6. INPUT • 例如老虎，則input四張圖(c1~c4) • 找出最好的match • 使用最好的objimg畫出框來

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