scalable salient motions detection from skeletal motion capture data
DESCRIPTION
Scalable Salient Motions Detection from Skeletal Motion Capture Data. Samah Ramadan. Outline. Introduction Literature Review Singular Value Decomposition Salient Motion Detection Results Conclusions. Introduction. Applications of human motion analysis - PowerPoint PPT PresentationTRANSCRIPT
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Scalable Salient Motions Scalable Salient Motions Detection from Skeletal Detection from Skeletal
Motion Capture DataMotion Capture Data
Samah RamadanSamah Ramadan
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OutlineOutline
IntroductionIntroduction Literature ReviewLiterature Review Singular Value DecompositionSingular Value Decomposition Salient Motion DetectionSalient Motion Detection ResultsResults ConclusionsConclusions
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IntroductionIntroduction
Applications of human motion Applications of human motion analysisanalysis Reconstruction of 3D models of humansReconstruction of 3D models of humans Gait analysis and activity recognitionGait analysis and activity recognition Motion captureMotion capture
Growing need for compact motion Growing need for compact motion representationrepresentation Motion summarizationMotion summarization Key frame extractionKey frame extraction
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Literature ReviewLiterature Review
Hand-drawn illustrations, Hand-drawn illustrations, storyboards and comic booksstoryboards and comic books
Speedlines, flow ribbons and opacity Speedlines, flow ribbons and opacity modulationmodulation
Dynamic Glyphs Dynamic Glyphs Streamline placementStreamline placement Curve simplificationCurve simplification Replicated multidimensional scalingReplicated multidimensional scaling
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Singular Value Singular Value DecompositionDecomposition
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Salient Motion DetectionSalient Motion Detection
Human Joint Configuration
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Salient Motion DetectionSalient Motion Detection
BVH FilesBVH FilesHIERARCHYROOT Hips{
OFFSET 0.00 0.00 0.00CHANNELS 6 Xposition Yposition Zposition Zrotation Xrotation YrotationJOINT Chest{
OFFSET 0.00 5.21 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT Neck{
OFFSET 0.00 18.65 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT Head{
OFFSET 0.00 5.45 0.00CHANNELS 3 Zrotation Xrotation YrotationEnd Site {
OFFSET 0.00 3.87 0.00}
}}JOINT LeftCollar{
OFFSET 1.12 16.23 1.87CHANNELS 3 Zrotation Xrotation YrotationJOINT LeftUpArm{
OFFSET 5.54 0.00 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT LeftLowArm{
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OFFSET 0.00 -11.96 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT LeftHand{
OFFSET 0.00 -9.93 0.00CHANNELS 3 Zrotation Xrotation YrotationEnd Site {
OFFSET 0.00 -7.00 0.00}
}}
}}JOINT RightCollar{
OFFSET -1.12 16.23 1.87CHANNELS 3 Zrotation Xrotation YrotationJOINT RightUpArm{
OFFSET -6.07 0.00 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT RightLowArm{
OFFSET 0.00 -11.82 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT RightHand{
OFFSET 0.00 -10.65 0.00CHANNELS 3 Zrotation Xrotation YrotationEnd Site {
OFFSET 0.00 -7.00 0.00}
}}
}}
}JOINT LeftUpLeg{
OFFSET 3.91 0.00 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT LeftLowLeg{
OFFSET 0.00 -18.34 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT LeftFoot{
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OFFSET 0.00 -17.37 0.00CHANNELS 3 Zrotation Xrotation YrotationEnd Site {
OFFSET 0.00 -3.46 0.00}
}}
}JOINT RightUpLeg{
OFFSET -3.91 0.00 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT RightLowLeg{
OFFSET 0.00 -17.63 0.00CHANNELS 3 Zrotation Xrotation YrotationJOINT RightFoot{
OFFSET 0.00 -17.14 0.00CHANNELS 3 Zrotation Xrotation YrotationEnd Site {
OFFSET 0.00 -3.75 0.00}
}}
}}MOTIONFrames: 2Frame Time: 0.033333 8.03 35.01 88.36 -3.41 14.78 -164.35 13.09 40.30 -24.60 7.88 43.80 0.00 -3.61 -41.45 5.82 10.08 0.00 10.21 97.95 -23.53 -2.14 -101.86 -80.77 -98.91 0.69 0.03 0.00 -14.04 0.00 -10.50 -85.52 -13.72 -102.93 61.91 -61.18 65.18 -1.57 0.69 0.02 15.00 22.78 -5.92 14.93 49.99 6.60 0.00 -1.14 0.00 -16.58 -10.51 -3.11 15.38 52.66 -21.80 0.00 -23.95 0.00 7.81 35.10 86.47 -3.78 12.94 -166.97 12.64 42.57 -22.34 7.67 43.61 0.00 -4.23 -41.41 4.89 19.10 0.00 4.16 93.12 -9.69 -9.43 132.67 -81.86 136.80 0.70 0.37 0.00 -8.62 0.00 -21.82 -87.31 -27.57 -100.09 56.17 -61.56 58.72 -1.63 0.95 0.03 13.16 15.44 -3.56 7.97 59.29 4.97 0.00 1.64 0.00 -17.18 -10.02 -3.08 13.56 53.38 -18.07 0.00 -25.93 0.00
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Salient Motion DetectionSalient Motion Detection
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Salient Motion DetectionSalient Motion Detection
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Salient Motion DetectionSalient Motion Detection
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Salient Motion DetectionSalient Motion Detection
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Salient Motion DetectionSalient Motion Detection
Sliding Window SVDSliding Window SVD
x i-N+1 x i-N+2 …….. x i x i+1 …….. x T
Window size N
Compute SVD and get the rank ri
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Salient Motion DetectionSalient Motion Detection
Sliding Window SVDSliding Window SVD
x i-N+1 xi-N+2 …….. x i x i+1 …….. x T
Window size N
Compute SVD and get the rank ri+1
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Salient Motion DetectionSalient Motion Detection
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Joint angels feature vectorJoint angels feature vector
Salient Motion DetectionSalient Motion Detection
Absolute location feature vectorAbsolute location feature vector
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Salient Motion DetectionSalient Motion Detection
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ResultsResults
Code, paper and dataCode, paper and data http://www.umiacs.umd.edu/http://www.umiacs.umd.edu/
~sramadan/SalientMotionProject.htm~sramadan/SalientMotionProject.htm
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ConclusionsConclusions
Extracting salient motion is an Extracting salient motion is an important problem in computer important problem in computer graphics, computer vision, etc.graphics, computer vision, etc.
SVD can be used to extract salient SVD can be used to extract salient motion framesmotion frames
Absolute position features are better Absolute position features are better than joint angle features in than joint angle features in representing the motion.representing the motion.
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AcknowledgmentAcknowledgment
Dr. Amitabh VarshneyDr. Amitabh Varshney Dr. Dianne O’LearyDr. Dianne O’Leary Youngmin KimYoungmin Kim