Publication

Rotation and scale invariant shape representation and recognition using Matching Pursuit

Abstract

Using a low-level representation of images, like matching pursuit, we introduce a new way of describing objects through a general description using a translation, rotation, and isotropic scale invariant dictionary of basis functions. We then use this description as a predefined dictionary of the object to conduct a shape recognition task. We show some promising results for the detection with simple shapes.

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Related concepts (27)
Harris affine region detector
In the fields of computer vision and , the Harris affine region detector belongs to the category of feature detection. Feature detection is a preprocessing step of several algorithms that rely on identifying characteristic points or interest points so to make correspondences between images, recognize textures, categorize objects or build panoramas. The Harris affine detector can identify similar regions between images that are related through affine transformations and have different illuminations.
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