Data processing: database and file management or data structures – Database and file access – Preparing data for information retrieval
Reexamination Certificate
2011-02-15
2011-02-15
Le, Debbie (Department: 2168)
Data processing: database and file management or data structures
Database and file access
Preparing data for information retrieval
C707S803000, C382S224000
Reexamination Certificate
active
07890512
ABSTRACT:
Images are automatically annotated using semantic distance learning. Training images are manually annotated and partitioned into semantic clusters. Semantic distance functions (SDFs) are learned for the clusters. The SDF for each cluster is used to compute semantic distance scores between a new image and each image in the cluster. The scores for each cluster are used to generate a ranking list which ranks each image in the cluster according to its semantic distance from the new image. An association probability is estimated for each cluster which specifies the probability of the new image being semantically associated with the cluster. Cluster-specific probabilistic annotations for the new image are generated from the manual annotations for the images in each cluster. The association probabilities and cluster-specific probabilistic annotations for all the clusters are used to generate final annotations for the new image.
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Hua Xian-Sheng
Li Shipeng
Mei Tao
Wang Yong
Le Debbie
Lyon Richard T.
Lyon & Harr LLP
Microsoft Corporation
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