| Autor: |
Jörn Schulz, James Stephen Marron, Junpyo Hong, James Damon, Jiyao Wang, Zhiyuan Liu, Liyun Tu, Sungkyu Jung, Beatriz Paniagua, Ankur Sharma, Stephen M. Pizer, Hyo-young Choi, Jared Vicory |
| Rok vydání: |
2020 |
| Předmět: |
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| Popis: |
Skeletal models that are structurally medial provide effective object representations. This is because they include not only locations but also boundary directions and object widths. We present a skeletal object representation that we call “quasimedial” because geometric properties associated with Blum's [1] medial axis are relaxed to allow the skeleton to have a pre-specified amount of branching and thus to support statistical analysis. We call this form of object representation the s-rep. We explain how such models can be automatically determined from object boundary data in a way that a) avoids boundary noise, b) implies a boundary that closely fits the input boundary, and c) well recognizes shape correspondences across cases. We also explain how to use Riemannian geometry to estimate probability distributions from a sample of s-reps and to find ways to classify s-reps between two categories as trained from s-reps in each class. Finally, we describe various evidence that shows the relative strengths of s-reps vs. other object representations; we also discuss shortcomings of s-reps. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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