Signal acquisition, Pre-processing and Normalization
- Motion capture (MoCap) systems to extract 3D joint positions by using markers and high precision camera array.
- Microsoft Kinect or Leap Motion sensor: Shotton algorithm largely eases the task of extracting 3D joint positions.
- Pen-based and Multi-Touch Capture on touch screen: smartphone, tablet PC and tangible surface which support simultaneous participation of multiple users
- Morphology normalisation pre-processing
- Joint trajectory modelling
- 2D and 3D feature extraction
- Sub-stroke representation
- Temporal, shape and motion relation between Sub-stroke
Artificial Intelligence for 2D and 3D Action recognition
- Eager and lazy Recognition
- Skeleton-based human action recognition
- Several Recognition and Machine Learning Approaches:
- Graph modelling, matching and embedding algorithm
- Dynamic Time Warping (DTW)
- Hidden Markov Model (HMM)
- Support Vector Machine (SVM)
- Neural Network (NN)
- Reject Option…
2D and 3D Segmentation and action detection
- Direct manipulation and indirect commands
- Early detection of an action, in an unsegmented stream
- Temporal segmentation methods
- Sliding Window approach
Human-centered design (ISO 9241-210) and test protocol
- The goal of the user-centered design process is to obtain a product that is functional, operational and satisfies the user applying humans factors, ergonomics, and knowledge and technics of usability.
- Test protocols
- Data analysis
Example and demo
Link between pattern recognition issues and human-machine interaction.
Link between 2D and 3D gesture recognition approaches.
Eric Anquetil (responsable), Richard Kulpa, Nathalie Girard