Toward semantic-based retrieval of visual information: a model-based approach

Youngchoon Park; Forouzan Golshani; Sethuraman Panchanathan

doi:10.1117/12.473050

1 July 2002 Toward semantic-based retrieval of visual information: a model-based approach

Youngchoon Park, Forouzan Golshani, Sethuraman Panchanathan

Proceedings Volume 4862, Internet Multimedia Management Systems III; (2002) https://doi.org/10.1117/12.473050
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States

Abstract

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Citation Download Citation

Youngchoon Park, Forouzan Golshani, and Sethuraman Panchanathan "Toward semantic-based retrieval of visual information: a model-based approach", Proc. SPIE 4862, Internet Multimedia Management Systems III, (1 July 2002); https://doi.org/10.1117/12.473050

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KEYWORDS

Visualization

Visual process modeling

Classification systems

Image classification

Image retrieval

Information visualization

Data modeling

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