Critical Nets and Beta-Stable Features for Image Matching

10 years 6 months ago
Critical Nets and Beta-Stable Features for Image Matching
Abstract. We propose new ideas and efficient algorithms towards bridging the gap between bag-of-features and constellation descriptors for image matching. Specifically, we show how to compute connections between local image features in the form of a critical net whose construction is repeatable across changes of viewing conditions or scene configuration. Arcs of the net provide a more reliable frame of reference than individual features do for the purpose of invariance. In addition, regions associated with either small stars or loops in the critical net can be used as parts for recognition or retrieval, and subgraphs of the critical net that are matched across images exhibit common structures shared by different images. We also introduce the notion of beta-stable features, a variation on the notion of feature lifetime from the literature of scale space. Our experiments show that arc-based SIFT-like descriptors of beta-stable features are more repeatable and more accurate than compet...
Added 11 Jul 2010
Updated 11 Jul 2010
Type Conference
Year 2010
Where ECCV
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