Relevance feedback for human motion retrieval using a boosting approach.
Songle ChenZhengxing SunYan ZhangQian LiPublished in: Multim. Tools Appl. (2016)
Keyphrases
- human motion
- relevance feedback
- information retrieval systems
- document retrieval
- human body
- image retrieval
- query expansion
- motion capture
- retrieval model
- retrieval framework
- retrieval process
- information retrieval
- image sequences
- motion sequences
- optical motion capture
- body parts
- spatio temporal
- cbir systems
- video sequences
- human motion tracking
- active learning
- human actions
- motion recognition
- human motion analysis
- three dimensional
- machine learning
- motion synthesis
- motion capture data
- gait recognition
- image database
- human pose
- visual data
- human movement
- dynamical model
- humanoid robot
- human movements
- test collection
- articulated objects
- articulated motion
- visual features
- motion history images
- retrieval systems