Shape Representaton Robust to the Sketchng Order Usng Dstance Map and Drecton Hstogram Department of Computer Scence Yonse Unversty Kwon Yun
CONTENTS Revew Topc Proposed Method System Overvew Sketch Normalzaton Spatal Informaton usng Dstance Map Drecton Hstogram Sketch Recognton Experment Database Expermental Result Demo Academc Actvty Q &A
Revew Topc The Goal Fnd shape representaton method to recognze handwrtng sketches drawn on Tablet PC Contrbuton Robust to the sketchng order Proposed Method Spatal Informaton usng Dstance map Drectonal Informaton usng Drecton Hstogram
Proposed Method System Overvew
Proposed Method Sketch Normalzaton Sketch Normalzaton The reason of normalzaton On-lne handwrtten sketches have large varaton Need to remove noses Method Control Pont Detecton Lne and Curve Fttng Aspect Rato Normalzaton
Proposed Method Sketch Normalzaton Control Pont Detecton A Input Stroke S s the a stroke N s the total number of nput ponts wthn a stroke S S A Control Pont C s the control pont 21 P,, P P 1 N, It s the vertex at whch dramatcally change the drecton, such as corner and curve C S
Proposed Method Sketch Normalzaton Control Pont Detecton The dot product 1. S s the a stroke, N s the total number of nput ponts wthn a stroke S 2. C P 0 3. For = 1 to N 1. Compute the dot product D PC PC where T 2. If D() < Threshold C C NC NC PC NC P P P C P P 1
Proposed Method Sketch Normalzaton Control Pont Detecton
Proposed Method Sketch Normalzaton Lne and Curve Fttng Method Classfy each control pont par as a lne or a curve L 1 ~ 1 f P P S N 0 Beautfcaton ~ P T 1 otherwse N P P Lne : Draw lne usng the start and end pont of the par Curve : Draw curve usng a quadratc Bezer curve 1 where P N P 1
Proposed Method Sketch Normalzaton Lne and Curve Fttng
Proposed Method Sketch Normalzaton Aspect Rato Normalzaton To reduce the effect of dfferent aspect rato. Interpolate wth the scale rato whch adjusts the wdth and heght of sketch nto m and n Interpolated Sketch s defned as Ι( x, y) mn
Proposed Method Sketch Normalzaton The result of Sketch Normalzaton
Proposed Method Feature Extracton Spatal Informaton usng Dstance Map Represents how far each pxel s from edges of object Rch feature about spatal nformaton of shape. Created by Dstance Transform Examples of dstance map
Proposed Method Feature Extracton Dstance Transform Start wth zero-nfnty mage : set each edge pxel to 0 and each non-edge pxel to nfnty. Make 2 passes over the mage wth a mask: Forward, from left to rght and top to bottom Backward, from rght to left and from bottom to top For each poston of mask on mage, V,j = mnmum(v -1,j-1 +d2,v -1,j +d1,v -,j+1 +d2, v,j-1 +d1,v,j ) Forward Mask Backward Mask Example of forward scan
Proposed Method Feature Extracton Spatal Informaton usng Dstance Map Orgnal Chamfer Dstance Lack robustness to a large shape varaton Just use nformaton of edge pxels as a spatal nformaton
Proposed Method Feature Extracton Drecton hstogram The factor of consderaton The same shape can be drawn wth dfferent order by dfferent person How to solve ths problem Algn between neghbors of samplng ponts as the regular rule (a) Horzontal (b) Vertcal (c) Dagonal
Proposed Method Feature Extracton Drecton hstogram Compute drecton Angle quantzes as n level Make drecton hstogram n 1 dmenson vector x x y y 1 1 1 tan ) D( 2 D 0, 9 0 18, tan ) D( 1 1 1 D x x y y
Proposed Method Sketch Recognton Matchng Database Feature Extracton Database Normalzed Sketch...... 504010 Eucldean Dstance 504010...
Experment - Database Database 1 : Freehand sketch We gve 28 shapes to 12 person let them draw the shapes by usng the pen of Tablet PC. Each person repeatedly drew each shape 3 tmes Fnally, we collected the total 1008(28123) shapes. Database 2 : Numerc symbol We gve 0~9 number to 40 person let them draw the shapes by usng the pen of Tablet PC. Each person repeatedly drew each shape 3 tmes Fnally, we collected the total 1200(40103) shapes.
Experment - Database
Accuracy Expermental Result : Shape recognton 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 The proposed method Chamfer dstance 1 2 3 4 5 6 7 8 9 10 Subjects
Accuracy Expermental Result : Shape recognton 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Spatal + Drecton Spatal Drecton 1 2 3 4 5 6 7 8 9 10 Subjects
Expermental Result : Shape recognton 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 Spatal+Curvature Spatal Curvature
Expermental Result : Shape recognton Average recognton rate n our database : 96.0%
Demo
Academc Actvty Submt Research Paper Internatonal Workshop on Structural and Syntactc Pattern Recognton (SSPR 2008) Orlando, Florda, USA, Dec 4-6, 2008 Internshp on Computer Vson & Pattern Recognton Partcpate n the project of sketch recognton wth Mcrosoft Always, stay n the lab Partcpate n lab meetng & lab events
Q & A Any questons?
Thanks for your attenton! Department of Computer Scence Yonse Unversty Kwon Yun