finger detection evaluation system
DESCRIPTION
Finger detection evaluation system. Su-ting, Chuang. Outline. Introduction Related work Hardware configuration Finger Detection system Optimal parameter estimation framework Conclusion. Outline. Introduction Related work Hardware configuration Finger Detection system - PowerPoint PPT PresentationTRANSCRIPT
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Finger detection evaluation system
Su-ting, Chuang
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OutlineIntroductionRelated workHardware configurationFinger Detection systemOptimal parameter estimation frameworkConclusion
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OutlineIntroductionRelated workHardware configurationFinger Detection systemOptimal parameter estimation frameworkConclusion
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IntroductionMotivation
Evaluate components in finger detection systems
Verify and improve performance of finger detection systems
MethodDevelop an optimal parameter estimation
frameworkUse most prevalent finger detection system as
testbed Touchlib
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OutlineIntroductionRelated workHardware configurationFinger Detection systemOptimal parameter estimation frameworkConclusion
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Related WorkFTIR (Frustrated Total Internal Reflection)
J. Y. Han, “Low-cost multi-touch sensing through frustrated total internal reflection," in Proceedings of the 18th annual ACM symposium on User interface software and technology (UIST '05). New York, NY, USA: ACM Press, 2005, pp. 115-118.
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Related WorkDI (Diffused Illumination)
J. Rekimoto and N. Matsushita, “Perceptual surfaces: Towards a human and object sensitive interactive display," Workshop on Perceptural User Interfaces (PUI'97), 1997.
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Related WorkTouchLib
A multi-touch development kit
Finger detection processing flow chartBackgroundSubtraction
SimpleHighpass ScaleMono Threshold
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OutlineIntroductionRelated workHardware configurationFinger Detection systemOptimal parameter estimation frameworkConclusion
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Hardware configurationTable setup
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Hardware configurationOrder of diffuser layer and touch-glass layer
Diffuser layer
IR illuminatorIR camera
spot
IR illuminatorIR camera
Touch-glass layer
IR camera
spot
IR camera
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Hardware configurationProblem:
IR rays will be reflected by the touch-glass and resulting hot spot regions in camera views
Solution:Use other cameras to recover the regions
which are sheltered by IR spots
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OutlineIntroductionRelated workHardware configurationFinger Detection systemOptimal parameter estimation frameworkConclusion
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Detection system
IR cam
Pre-processing
Imageprocessin
g
FingerAnalyzing
DataAssociatio
n
DataTransmissio
n
IR cam GPU
CPU
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Detection systemPre-processing
ImageFusion(Blend)
IR Camera
IR camera
Undistortion
Undistortion
HomoWarp
HomoWarp
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Pre-processingUndistortion
Undistort foreground objectsWarp
Unify finger size among different position of table
Image fusionMask hot spots and recover them from the
other camera imageFinger at border won’t be discard
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Pre-processingAdvantage of implementing on GPU
Increase performance High frame rate
Preserve CPU for application computation Enable detection system and interactive application
on the same computer Reduce unsynchronized problem among different
computers
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Detection systemImage processing
BackgroundSubtraction Normalization Simple
HighpassMono Threshold
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Image processingNormalization
Motivation Eliminate influence due to non-uniform lighting
condition Various finger touch response
Hard to decide a good thresholdMethod
Model distribution of IR illumination Use specific material to simulate foreground Calculate each pixel’s dynamic range
Stretch dynamic range to 0-255
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Finger AnalyzingConnected componentfinger size evaluation
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Data associationFingertip matching
Matching fingertips among framesUsing bipartite algorithm
Fingertip trackingSmooth detected results and fix lost resultsUsing Kalman filter
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OutlineIntroductionRelated workHardware configurationDetection systemOptimal parameter estimation frameworkConclusion
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Optimal parameters estimation frameworkMotivation
Find optimal parameters for finger detection system
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Optimal parameters estimation frameworkProcedure
Define parameters for finger detection systemCollect samples
Various finger size Various hand gesture
Search optimal parameters Verify performance of all possible parameter
combinations
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Optimal parameters estimation frameworkCollect samples
Task Soft /Hard touch Vertical/Oblique touch Various fingers
Sample set Each task has 2x2x5 samples
Sample collection Step-by-step instruction Straightforward UI design
Finger touch position
5timer
Instructions….
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Optimal parameters estimation frameworkSearch optimal parameters
Exhaustive search Test various parameter combination in each set
Step Each parameter combination
Detect finger touch Verify detection result
Calculate error rate
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Optimal parameters estimation frameworkDetection systemframe
Optimal parameter finder
Parameter Set
Detection Result
GroundTruth
OptimalParameter Set
VerifyNext Parameter Set
Generator
DetectionResult
GroundTruth
Error Rate
Parameter Set
Sampleset
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OutlineIntroductionRelated workHardware configurationDetection systemOptimal parameter estimation frameworkConclusion
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Thanks for your attention