Relevance feedback for real-world human action retrieval.
Simon JonesLing ShaoJianguo ZhangYan LiuPublished in: Pattern Recognit. Lett. (2012)
Keyphrases
- relevance feedback
- human actions
- real world
- action recognition
- image retrieval
- retrieval framework
- document retrieval
- information retrieval systems
- retrieval accuracy
- retrieval precision
- query expansion
- retrieval model
- spatio temporal
- activity recognition
- visual features
- cbir systems
- retrieval process
- human motion
- space time
- human activities
- video database
- human perception
- motion recognition
- low level features
- action classification
- video sequences
- relevant documents
- data sets
- data mining
- active learning
- recognizing actions
- recognition of human actions
- human pose
- retrieval systems
- image database
- high level
- three dimensional
- computer vision
- image classification
- language model
- viewpoint
- training data
- image sequences
- retrieved images