Recent Developments in Human Motion Analysis Liang Wang, Weiming Hu, Tieni u Tan Chinese Academy of Sciences, Beijing, People’s Republic of China 2002 Pattern Recognition
Dec 19, 2015
Recent Developments in Human Motion Analysis
Liang Wang, Weiming Hu, Tieniu Tan
Chinese Academy of Sciences, Beijing,
People’s Republic of China
2002 Pattern Recognition
Outline
• Potential application• Detection• Tracking• Behavior analysis• Future researches
Potential Applications
• Visual surveillance• Tracking and recognition techniques of face
and gait• Advanced user interface
• Control and command by speech, gestures, body poses, facial expressions, etc.
• Motion-based diagnosis and identification• Medical diagnosis, sports, orthopedic patient
s, choreography
Motion Detection
• Human detection aims at segmenting regions corresponding to people from the rest of an image.
• Motion segmentation• Background subtraction• Statistical methods• Temporal differencing• Optical flow
Motion Detection
• Object classification• The purpose of moving object classification is to pr
ecisely extract the region corresponding to people from all moving blobs obtained by the motion segmentation methods.
• Shape-based• NN classifier
• Motion-based• Periodic property• Residual flow
Human Tracking
• Useful mathematical tools• Kalman filter• Condensation algorithm• Dynamic Bayesian network
• Different classification• Hand, face, leg, whole body• Single-view, multiple-view, omni-directional view• 2-D, 3-D• Indoors, outdoors• Single human, multiple human, human groups• Moving, stationary• Monocular, stereo
Human Tracking
• Model-based• Stick figure (fig.)• 2-D contour (fig.)• Volumetric models (fig.)
• Region-based (fig.)• Active-contour-based (fig.)• Feature-based
Recognition and Description of Human Activities• Behavior understanding is to analyze an
d recognize human motion patterns, and to produce high-level description of actions and interactions.
• General techniques• Dynamic time warping (DTW)• Hidden Markov models (HMMs)• Neural network (NN)
Recognition and Description of Human Activities• Action recognition
• Template matching• State-space approaches
• Semantic description
Further Researches
1) Segmentation
2) Occlusion handling
3) 3-D modeling and tracking
4) Use of multiple cameras
5) Action understanding
6) Performance evaluation