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Gesture Recognition A lot of applications require accurate understanding of human gestures Sign language reading and dancing Some tasks may require the detailed sequence of the gesture action Kinect Sports We tackle the problem of gesture recognition + alignment
Xbox Kinect Pipeline: Skeleton Correction & Alignment Depth Image Background Removal Skeleton Extraction Skeleton Correction & Alignment
Page 1 and 2: Microsoft Research Asia Update Hsia
Page 3 and 4: Microsoft Research Research lab loc
Page 5 and 6: People and Research Areas Hsiao-Wue
Page 7 and 8: Research Groups Hardware Computing
Page 9 and 10: Research Updates Natural User Inter
Page 11 and 12: Kinect based Object Digitization Si
Page 13 and 14: Comparisons 35,862 Triangles 36MB M
Page 15: Avatar Kinect Facial expression tra
Page 19 and 20: Skeleton/Gesture Alignment •The s
Page 21 and 22: Output Distribution Model Random fo
Page 23 and 24: Qualitative Results
Page 25 and 26: Kinect Based 3D Face Avatar 3D face
Page 27 and 28: Kinect Based 3D Face Avatar (Fang Y
Page 29 and 30: Goal: 3D Hair from Single Image Sin
Page 31 and 32: Result Single portrait image + user
Page 33 and 34: Strand Tracing
Page 35 and 36: 3D Strands: hair volume Additional
Page 37 and 38: Portrait Pop-ups: layers completion
Page 39 and 40: Hairstyle Replacement Build pop-up
Page 41 and 42: Hairstyle Replacement: more results
Page 43 and 44: Limitations Not a complete 3D model
Page 45 and 46: 3D Hair Replacement
Page 47 and 48: Research Updates Search and online
Page 49 and 50: What Are Attributes? Clipart Linedr
Page 51 and 52: What Are Attributes? Simple Backgro
Page 53 and 54: Color/Clipart/Linedrawing Filter
Page 55 and 56: Color Filter Examples dog + red Red
Page 57 and 58: Color Filter Examples sunset + blue
Page 59 and 60: Intention Analysis (w/o Query Objec
Page 61 and 62: Original Images
Page 63 and 64: Our Solution • Salient object det
Page 65 and 66: Our Solution • Salient object det
Page 67 and 68:
BMW + blue
Page 69 and 70:
BMW+ red
Page 71 and 72:
dog
Page 73 and 74:
dog + blue
Page 75 and 76:
dog + black
Page 77 and 78:
forest
Page 79 and 80:
forest + red
Page 81 and 82:
sunset
Page 83 and 84:
sunset + green
Page 85 and 86:
tulips
Page 87 and 88:
tulips + purple
Page 89 and 90:
Taylor Swift
Page 91 and 92:
Taylor Swift + red
Page 93 and 94:
Important Filters Usage on image se
Page 95 and 96:
Cascaded Filtering Simple Backgroun
Page 97 and 98:
Cascaded Filtering Web Images Backg
Page 99 and 100:
Cascaded Filtering Shape Filter: Pr
Page 101 and 102:
Cascaded Filtering Texture Filter:
Page 103 and 104:
Page 105 and 106:
Cascaded Filtering Photo Filter: Cl
Page 107 and 108:
Cascaded Filtering Text Filter: Tex
Page 109 and 110:
Page 111 and 112:
Relevance ≠ Clipart Relevance Ran
Page 113 and 114:
Results without Clipart Specific Te
Page 115 and 116:
Results without Clipart Specific Te
Page 117 and 118:
Bing Clipart Filter • Visual filt
Page 119:
Results
Page 124 and 125:
Cascaded Filtering Text Filter: Fil
Page 126 and 127:
Motivation Visual quality is import
Page 128 and 129:
Integrate Visual Features Color- Hi
Page 130 and 131:
Image Quality Related Attributes Pe
Page 132 and 133:
Image Quality Related Attributes Ob
Page 134 and 135:
Image Quality Related Attributes Im
Page 136 and 137:
Image Quality Related Attributes Ge
Page 138 and 139:
Comparison Results Old results (que
Page 140 and 141:
Comparison Results Old results (que
Page 142 and 143:
Research Updates Data Intensive Com
Page 144 and 145:
Urban Computing Improving Sensing U
Page 146 and 147:
1. GPS trajectories of 33,000 taxis
Page 148 and 149:
3. Ticketing data of public transpo
Page 150 and 151:
5. Real estate market
Page 152 and 153:
7. POI Data (2007 - 2012)
Page 154 and 155:
Discover Regions of Different Funct
Page 156 and 157:
Applications • Calibrating urban
Page 158 and 159:
Methodology Overview Mapping from r
Page 160 and 161:
Annotation of Territories Emerging
Page 162 and 163:
Research Updates CS Fundamentals Th
Page 164 and 165:
GPUs vs. Programmers GPU architectu
Page 166 and 167:
Research on BSGP (2007~now) Compile
Page 168 and 169:
Contribution to Community BSGP down
Page 170 and 171:
Motivation Growing demand for fineg
Page 172 and 173:
Key Problem How to efficiently buil
Page 174 and 175:
Enabling Walking-based Collection I
Page 176 and 177:
Path/Trace list # of Effective turn
Page 178 and 179:
End-to-end Evaluation* 100% 95% 90%
Page 180 and 181:
An Illustrative Example Start Actua
Page 182 and 183:
Conclusion MSRA follows the same mi
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