Multimodal Point Distribution Model for Anthropological Landmark Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00110475" target="_blank" >RIV/00216224:14330/19:00110475 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICIP.2019.8803252" target="_blank" >http://dx.doi.org/10.1109/ICIP.2019.8803252</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICIP.2019.8803252" target="_blank" >10.1109/ICIP.2019.8803252</a>
Alternative languages
Result language
angličtina
Original language name
Multimodal Point Distribution Model for Anthropological Landmark Detection
Original language description
While current landmark detection algorithms offer a good approximation of the landmark locations, they are often unsuitable for the use in biological research. We present multimodal landmark detection approach, based on Point distribution model that detects a larger number of anthropologically relevant landmarks than the current landmark detection algorithms. At the same time we show that improving detection accuracy of initial vertices, using image information, to which the Point distribution model is fitted, increases both the overall accuracy and the stability of the detected landmarks. We show results on data from the public FIDENTIS Database, created for the anthropological research, and compare them to the state-of-the-art landmark detection algorithms that are based on statistical shape models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
26th IEEE International Conference on Image Processing (ICIP2019)
ISBN
9781538662496
ISSN
1522-4880
e-ISSN
2381-8549
Number of pages
5
Pages from-to
2986-2990
Publisher name
Springer
Place of publication
Taipei, Taiwan
Event location
Taipei, Taiwan
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000521828603020