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Lecture 1 4. Previous Works. A target is assumed to be Scaled, Rotated Version Template With Edges Distorted. Problem: Target Image Search. Search on Images Database. Target. Template. Inspiration Jain et al [1] , “Object Matching Using Deformable Templates” Our Algorithm
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Lecture 14 Previous Works
A target is assumed to be Scaled, Rotated Version Template With Edges Distorted Problem: Target Image Search Search on Images Database Target Template
Inspiration Jain et al [1] , “Object Matching Using Deformable Templates” Our Algorithm Finding Hypotheses : MGHT Peak Clustering : Watershed Method Contour Matching : Smooth Membrane Fitting Methodology: An Overview Hypotheses 3 Peaks in 3D Hough Space Template Target Contours Rejected Hypothesis Rejected Hypothesis Accepted Hypothesis
r1, a1, q1, l1 r2, a2, q2, l2 r3, a3, q3, l3 r4, a4, q4, l4 0...19 15,180,195,99 9,179,219,101 8,177,216,102 9,176,198,100 20...39 17,160,23,5 14,159,38,7 18,161,175,62 15,162,195,95 30…49 19,165,31,53 20,170,8,52 22,167,15,52 18,159,158,12 … … … … … 340...359 23,105,346,11 24,103,165,11 21,102,346,18 22,104,195,24 Finding Candidate Target:Modified Generalized Hough • [Nimkerdpol and Madarasmi, 2001] • A line at the contour edge is extended in the g direction until it meets the other end of the contour • In MGHT, the relation between Dq (r,a,q,l) is stored as a linked list in R-Table, not as q (a,r) like in GHT
= 30-200 = -170 = 190 = 300-110 = 190 MGHT: Rotation/Scale
MGHT xc = x + S r cos (a + b) yc = y + S r sin (a + b) Rotation Factor: Scaling Factor : New ref. Point :
Watershed for Peak Clustering 1. Shed, by labeling, at the first level, calculate peaks of each label 2. Increase to higher level, shed again 2.1 Meet an area of previous level, shed to that area 2.2 Not meet any area of previous level, make a new area , calculate a new peak
Parameter : (Dx,Dy) or (u,v)range -7, -6, …,0,… 6, 7 Deformation : Contour Matching
Energy Function Matching Algorithm Update (u,v) :Gibbs Sampler with simulated annealing Template Target Edge
Experiment on Image Search Template Target Edge Map Result Hough Space
Experiment on Image Search 1st Match Hypotheses Target Edge 2nd Match 3rd Match 4th Match
Experiment on Image Search Template Target Edge Map Hough Space The Best Match
Threshold Selection: Guitar 1 2.705226 0.929011 3.986274 Template Target Edge Hypotheses Threshold : 1.0 - 2.6
Threshold Selection: Guitar 1 Template Target Edge Hypotheses Threshold : 1.0-1.6 1.755835 2.165488 0.965049
Threshold Selection: Vase 1 Template Hypotheses Edge Map Threshold : 1.2-1.6 5.074061 1.799267 1.114566
Threshold Selection: Vase 2 Template Target Edge Hypotheses 0.868600 0.879799 3.799124 Threshold : 0.9-3.6
Threshold Selection: Vase 3 Threshold : 1.5-3.2 Template Target Edge Hypotheses 1.293034 1.452130 3.364521 4.4185782
Experiment on Image Querying Database Search for Circle shape
Experiment on Image Querying Search for bulb shape Database
Conclusion • A deformation model • Contour Matching • A method for image search • Future work: large image database, efficient method for minimizing energy, coarse-and-fine approach to computer vison modules
Accurate 3-D surface map using stereo vision • This proposal research addresses 2 issues: • Find an accurate 3-D surface map using stereo vision • Combine surface from different views to a single 3-D object for CAD applications.
Combine surface from multiple views to a single 3-D object. To combine multiple view, we need to find the rotation and transformation matrices from each camera combined to the world or reference co-ordination system. ================== Rotation : 0.71220.70190.0130 Rotation : 0.0386-0.0207-0.9990 Rotation : -0.70100.7120-0.0418 Translation : 16.6342 Translation : 32.6633 Translation : 181.5649 ==================
A Relaxation Method for Shape from Contours • Input Contour Images: • Geodesics Contours Only • Developable Surface (No Folds/Twists) • Non-Accidental View • Place Grid Points in X and Y Direction to have Smooth • Draw Horizontal and Vertical Lines through Grid to Form a Regular Square Texture • Use Shape from Texture to Obtained Surface Normals
Experiment 2 Original Step 1 Step 2 Step 3