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In this paper, the matching of SIFT-like features [5] between images is studied. The goal is to decide which matches between descriptors of two datasets should be selected. This matching procedure is often a preliminary step towards some computer vision applications, such as object detection and image registration for instance. The distances between the query descriptors and the database candidates...
Exploiting geometric features, such as points, straight or curved lines and corners, plays an important role in object recognition. In this paper, we present a model-based recognition of 3D objects using intersecting lines. We concentrate on using perpendicular line pairs to test recognition of a parallelepiped model and represent the visible face of the object. From 2D images and point clouds, first,...
This paper presents an improved relaxation algorithm for image matching. The original relaxation algorithm includes two steps: rough matching and accurate matching. It usually is time-consuming for most practical problems. With the improved relaxation algorithm proposed in this paper, the number of matching points that take part in the next pass iteration can be reduced, consequently, the algorithm...
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