Towards Semantic Clustering : Grouping Image Visual Features Through Exploratory Factor Analysis - Narayanan, A/L N. Kulathu Ramaiyer; Lim, Phei Chin; Dayang Nurfatimah, Binti Awang Iskandar; Chiew, Kang Leng (2012)
Current image clustering schemes tend to cluster images based on similarity of low-level image visual features. Our previous work has demonstrated the need for organizing groups of low-level image visual features into composite feature sets that can then be mapped to semantically relevant abstractions. Symbolic terms such as wing ratio and tailed-wings and many more have been obtained from mapping clusters from a single-feature clustering and visual knowledge acquisition. Current focus is the explorations on the extraction and transformation of groupings of low-level image visual features into factor space before mapped to these meaningful terms. Preliminary results from exploratory factor analyses with different settings suggested the solution of forming four groups of features. The selected visual feature groupings have also been shown to correspond to the user-relevant symbolic terms. We hope to highlight these mapped relationships at the conference.