Work in progress in graphics recognition Mathieu Delalandre DAGMinar, 12th of May 2009, CVC, Barcelone, Spain

Plan  Symbol Recognition  Performance Evaluation  Content Based Image Retrieval

p2p2 p1p1 l1l1 l2l2 Symbol Recognition Vector Template MatchingLine Detection (HT) , ,12 0,41 1, Delta5.1Score 211.4Score 1 detected vectors model vectors **7 *6 *5 **4 *3 *2 *1 * detected vectors 7size0missed0false alarm 2split1merged4simple p1p1 L l1l1 l2l2 p2p2 vecteurs modèles vecteurs détectés dy 1 dx 1 dy 2 dx 2 L p L overlap p if dx 1  dx 2 < 0 or dy 1  dy 2 < 0 d1d1 d2d2 π/2π/2 π/2π/2 Build-up the matrix Detect cases Compute the distances

Symbol Recognition GREC’03 dataset (900 symbols) 0 π 2π2π 0 Π/2 Π θ1θ1 θ2θ2 Invariant to shifting Invariant to merging cases Robust to splitting (holes -> picks) Robust to slightly θ distorsion Context based signature for key primitives detection

Plan  Symbol Recognition  Performance Evaluation  Content Based Image Retrieval

Characterisation Groundtruth Groundtruthing Results Performance evaluation System Performance Evaluation c2c2 c1c1 M1M1 M2M2 M3M3 M4M4 C1C1 C2C2 C3C3 C4C4 L1L1 θ1θ1 p1p1 L2L2 θ2θ2 p2p2 p L  bounding box and control point alignment symbol model loaded symbol no selection on model full ? overflow ? selection on constraint overlap ? continue ? constraint stack empty ? building failure model and constraint symbol and constraint no yes building end yes (1) model and constraint selection (2) symbol loader (5) constraint checking (7) Stopping criterion (6) Space management positioned symbol (3) symbol control document generationsymbol positioning (4) shape positioning yes control shapes symbol loader symbol control shape positioning no new loop cleaning reproduction of domain-rules building use

datasetsimagessymbols models bags# floorplans# diagrams# queries# Symbol Models Building Engine (2) run (3) display (1) edit Background Image Performance Evaluation v0 x s  [0,1] y v max

Performance Evaluation Spotting/Recognition System Groundtruth Mapping Region Of Interest Characterization sofa skin tub door Labels r1 r2 r3 Ranks QBE truth results Learning truth results Single : a model line matches only with one detected line. Split : two model lines match with one detected line. Merge : a model line matches with two detected lines. False alarm : a detected line doesn't match with any model lines. Miss : a model line doesn't match with any detected lines. Mapping cases groundtruth ROI Domain definition of ROI SamplingShiftingSignature f localization point overlayed ROI 1.To put at a same level the systems’ results 2.Complexity of detection algorithm θ(n) with concave polygon 3.To limit the over segmentation results SESYD dataset (6 backgrounds, 100 plans, 2521 symbols) cg p θ L

Plan  Symbol Recognition  Performance Evaluation  Content Based Image Retrieval

Content Based Image Retrieval Wood plug (bottom view) printing 1 printing 2 printing 3 plug 1 plug 2 Vascosan 1555Marnef 1576 Printing house plug exchange duplicate Printings produced by a same plug with a 21 year gap Wood plug duplicate Max Mean Min RLERasterQuery (s) x2x2 x2x2 x2x2 x1x1 x1x1 x1x1 x2x2 x2x2 x1x1 line (y) image 1 line (y) image 2 x stack pointeur while x 2  x 1 handle image 2 while x 1  x 2 handle image 1

Content Based Image Retrieval query selection RLE 11 22 if  1 -  2 < 0 push x, cluster while  1 -  2 < 0 next Step 2 Step 1 Size (height, width) Density (foreground, background) Compression (foreground, background) Lowest picks N points selection numerical approximation cumulative curves derivatives 1 st and 2 sd