Title :
An Object- and User-Driven System for Semantic-Based Image Annotation and Retrieval
Author :
Djordjevic, D. ; Izquierdo, E.
Author_Institution :
Electr. Eng. Dept., Queen Mary Univ. of London
fDate :
3/1/2007 12:00:00 AM
Abstract :
In this paper, a system for object-based semi-automatic indexing and retrieval of natural images is introduced. Three important concepts underpin the proposed system: a new strategy to fuse different low-level content descriptions; a learning technique involving user relevance feedback; and a novel object based model to link semantic terms and visual objects. To achieve high accuracy in the retrieval and subsequent annotation processes several low-level image primitives are combined in a suitable multifeatures space. This space is modelled in a structured way exploiting both low-level features and spatial contextual relations of image blocks. Support vector machines are used to learn from gathered information through relevance feedback. An adaptive convolution kernel is defined to handle the proposed structured multifeature space. The positive definite property of the introduced kernel is proven, as essential condition for uniqueness and optimality of the convex optimization in support vector machines. The proposed system has been thoroughly evaluated and selected results are reported in this paper
Keywords :
content-based retrieval; image retrieval; indexing; relevance feedback; support vector machines; adaptive convolution kernel; image blocks; learning technique; natural images retrieval; object-based semiautomatic indexing; object-driven system; relevance feedback; semantic-based image annotation; spatial contextual relations; support vector machines; user-driven system; Context modeling; Convolution; Feedback; Fuses; Humans; Image retrieval; Indexing; Information retrieval; Kernel; Support vector machines; Content-based image retrieval; kernels on sets; relevance feedback; support vector machines;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2007.890634