Image and Video Analysis

WαSH Detector

WαSH: Weighted α-Shapes for Local Feature Detection

Depending on the application, local feature detectors should comply with properties that are often contradictory, e.g. distinctiveness vs. robustness. Providing a good balance is a standing problem in the field. In this direction, we propose a novel approach for \emph{local feature detection} starting from sampled edges and based on shape stability measures across the \emph{weighted a-filtration}, a computational geometry construction that captures the shape of a non-uniform set of points. Detected features are blob-like and include non-extremal regions as well as regions determined by cavities of boundary shape. The detector provides distinctive regions, while achieving high robustness in terms of \emph{repeatability} and \emph{matching score}, as well as competitive performance in a large scale image retrieval application.

(a) (b) (c) (d)

Figure 1. Feature detection based on a-shapes. (a) Input image. (b) Edge samples with assigned weights as squared radii (blue) and triangulation. Triangle colors denote distinct connected components of the a-complex. Detected features by: (c) WαSH detector and (d) MSER.


WαSH detection results on images from the bikes and Oxford Buildings datasets.

Repeatability, matching score and number of correct matches, on the bikes, boat, lauven and wall datasets.


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C. Varytimidis, K. Rapantzikos, Y. Avrithis. WαSH: Weighted α-Shapes for Local Feature Detection. In Proceedings of European Conference on Computer Vision (ECCV 2012), Florence, Italy, October 2012.
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C. Varytimidis, K. Rapantzikos, S. Kollias. Wα SH-ing visual repositories: searching Europeana using local features. In Proceedings of International Conference on Digital Signal Processing (DSP 2013), July 2013.
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C. Varytimidis, K. Rapantzikos, Y. Avrithis, S. Kollias. Improving local features by dithering-based image sampling. In Proceedings of Asian Conference on Computer Vision (ACCV 2014), Singapore, November 2014.
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C. Varytimidis, K. Rapantzikos, Y. Avrithis, S. Kollias. α-shapes for local feature detection. In Pattern Recognition, vol 50, no. 1, pp. 56-73, February 2016.
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[ Bibtex ] [ PDF ]