R
Rolf Lakämper
Researcher at University of Hamburg
Publications - 12
Citations - 2088
Rolf Lakämper is an academic researcher from University of Hamburg. The author has contributed to research in topics: Similarity measure & Similarity (geometry). The author has an hindex of 8, co-authored 12 publications receiving 2008 citations. Previous affiliations of Rolf Lakämper include Temple University.
Papers
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Proceedings ArticleDOI
Shape descriptors for non-rigid shapes with a single closed contour
TL;DR: This paper reports on the MPEG-7 Core Experiment CE-Shape, which gave a unique opportunity to compare various shape descriptors for non-rigid shapes with a single closed contour and found that a more theoretical comparison of these descriptors seems to be extremely hard.
Journal ArticleDOI
Shape similarity measure based on correspondence of visual parts
Longin Jan Latecki,Rolf Lakämper +1 more
TL;DR: This work applied a cognitively motivated similarity measure to shape matching of object contours in various image databases and compared it to well-known approaches in the literature, justifying that the shape matching procedure gives an intuitive shape correspondence and is stable with respect to noise distortions.
Journal ArticleDOI
Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution
Longin Jan Latecki,Rolf Lakämper +1 more
TL;DR: A novel rule is obtained, called the hierarchical convexity rule, which states that visual parts are enclosed by maximal convex (with respect to the object) boundary arcs at different stages of the contour evolution.
Journal ArticleDOI
Application of planar shape comparison to object retrieval in image databases
Longin Jan Latecki,Rolf Lakämper +1 more
TL;DR: Experimental results show that the shape matching procedure gives an intuitive shape correspondence and is stable with respect to noise distortions.
Book ChapterDOI
Polygon Evolution by Vertex Deletion
Longin Jan Latecki,Rolf Lakämper +1 more
TL;DR: A simple approach to evolution of polygonal curves that is specially designed to fit discrete nature of curves in digital images, which leads to simplification of shape complexity with no blurring (i.e., shape rounding) effects and no dislocation of relevant features.