Title :
Individual Image Retrieval Based on User Interest Model
Author :
Fujuan, Feng ; Zhaowen, Qiu
Author_Institution :
Coll. of Life Sci., Northeast Forestry Univ., Harbin, China
Abstract :
There exists a semantic gap between low-level visual feature and high-level semantics feature, and the accuracy of image semantics annotation depends greatly on the description of low-level visual feature. Taking this into consideration, user interest model is proposed in this paper, syncretizing color feature and texture feature into eigenvector, labeling image semantics information by using user interest model. Experiments show that user interest model can be successfully used in image semantics annotation and individual image retrieval.
Keywords :
eigenvalues and eigenfunctions; image retrieval; eigenvector; high level semantics feature; image retrieval; image semantics annotation; low level visual feature; user interest model; Computer science education; Data mining; Feature extraction; Forestry; Humans; Image retrieval; Information retrieval; Labeling; Layout; Shape; Image retrieval; Semantic gap; Semantics annotation; User interest model;
Conference_Titel :
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6388-6
Electronic_ISBN :
978-1-4244-6389-3
DOI :
10.1109/ETCS.2010.443