ADS lab NCKU1 Michael Maire, Pablo Arbelaez, Charless Fowlkes, and Jitendra Malik university of California, Berkeley – Berkeley university of California,

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Presentation transcript:

ADS lab NCKU1 Michael Maire, Pablo Arbelaez, Charless Fowlkes, and Jitendra Malik university of California, Berkeley – Berkeley university of California, Irvine - Irvine Using Contours to Detect and Localize Junctions in Natural Images 指導教授 : 李強教授 Reporter: P 王炳竣 P 方俞淵 P 陳柏嘉

ADS lab NCKU2 Outline Introduction flowchart Contour Detection ◦ Local contours ◦ Global Contours Detecting Junctions

ADS lab NCKU3 Introduction Contour Detection Application ◦ Image segment

ADS lab NCKU4 Introduction Junctions Detection Application

ADS lab NCKU5 flowchart Image Local contours Global contours Global contours Result Contour Detection: Junctions Detection: Contour Detection Result Contour Detection Result

ADS lab NCKU6 Contour Detection: Local contours Boundary Cues Model PbPb Brightness Color Texture Goal: learn the posterior probability of a boundary P b (x,y,  ) from local information only Cue Combination Martin, Fowlkes, Malik PAMI 04

ADS lab NCKU7 Contour Detection: Local contours Line Detection 梯度運算子 (Gradient Operator)

Individual Features Brightness Gradient BG (x,y,r,  ) Color Gradient CG (x,y,r,  ) Texture Gradient TG (x,y,r,  ) ADS lab NCKU8 Contour Detection: Local contours These are combined using logistic regression  r (x,y)

ADS lab NCKU9 Contour Detection: Global Contours Node : the points in the feature space Graph: G(V, E) Edge : between every pair of points Weight(Wij) Image segmentation (high-level cues)

How to partition the Graph: ADS lab NCKU10 Contour Detection: Global Contours Partition graph so that similarity within group is large and similarity between groups is small -- Normalized Cuts [Shi & Malik 97]

ADS lab NCKU11 Contour Detection: Global Contours

ADS lab NCKU12 Contour Detection: Global Contours

ADS lab NCKU13 Contour Detection: Combine Global ContoursLocal contours

1.Estimate the optimal junction location by minimizing its weighted distance from the contours 2.Update the weight of each contour in order to select only those contours passing close to the junction ADS lab NCKU14 Detecting Junctions

ADS lab NCKU15 Detecting Junctions

ADS lab NCKU16 Demo

ADS lab NCKU17 Conclusions & Comment 上課時呈現 ^__^