DocumentCode
3298743
Title
Learning the semantics of words and pictures
Author
Barnard, Kobus ; Forsyth, David
Author_Institution
Comput. Div., California Univ., Berkeley, CA, USA
Volume
2
fYear
2001
fDate
2001
Firstpage
408
Abstract
We present a statistical model for organizing image collections which integrates semantic information provided by associate text and visual information provided by image features. The model is very promising for information retrieval tasks such as database browsing and searching for images based on text and/or image features. Furthermore, since the model learns relationships between text and image features, it can be used for novel applications such as associating words with pictures, and unsupervised learning for object recognition
Keywords
image retrieval; information retrieval; unsupervised learning; visual databases; associate text; database browsing; image collections; image features; information retrieval tasks; object recognition; semantic information; unsupervised learning; visual information; Image databases; Image retrieval; Image segmentation; Information retrieval; Object recognition; Organizing; Predictive models; Spatial databases; Statistics; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7695-1143-0
Type
conf
DOI
10.1109/ICCV.2001.937654
Filename
937654
Link To Document