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Scalable Salient Motions Scalable Salient Motions Detection from Skeletal Detection from Skeletal
Motion Capture DataMotion Capture DataSamah 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 analysisApplications of human motion analysis
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 Files
HIERARCHYROOT 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