IR_URFS_VF: image recommendation with user relevance feedback session and visual features in vertical image search.
D. SejalD. AbhishekK. R. VenugopalS. S. IyengarL. M. PatnaikPublished in: Int. J. Multim. Inf. Retr. (2016)
Keyphrases
- image search
- relevance feedback
- visual features
- image retrieval
- relevant images
- web images
- image collections
- image classification
- user feedback
- web image search
- low level visual features
- query expansion
- visual attributes
- image content
- image annotation
- cbir systems
- visual content
- information retrieval systems
- low level features
- retrieval process
- visual information
- active learning
- image representation
- visual similarity
- visual and textual features
- web image retrieval
- textual and visual features
- information retrieval
- semantic gap
- image database
- image features
- image data
- key frames
- image matching
- low level
- high level
- labeled images
- retrieval model
- recommender systems
- semantic concepts
- video sequences
- keywords
- feature extraction
- computer vision