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TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

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research:shape_analysis [2015/05/20 09:42]
rodola
research:shape_analysis [2020/10/06 10:08] (current)
Christiane Sommer
Line 1: Line 1:
 ====== Shape Analysis ====== ====== Shape Analysis ======
- 
-Contact: [[members:rodola|Dr. Emanuele Rodolà]] 
  
 Over the last years, the availability of devices for the acquisition of three-dimensional data like laser-scanners, [[:research:RGB-D Sensors (Kinect)]] or medical imaging devices has dramatically increased. This brings about the need for efficient algorithms to analyze three-dimensional shapes. Over the last years, the availability of devices for the acquisition of three-dimensional data like laser-scanners, [[:research:RGB-D Sensors (Kinect)]] or medical imaging devices has dramatically increased. This brings about the need for efficient algorithms to analyze three-dimensional shapes.
Line 7: Line 5:
 Our research is focused on reliable and efficient methods for the automatic interpretation of non-rigid three-dimensional shapes. In particular, we have been working on novel approaches to **Shape Matching** and on the design of **Feature Descriptors**. Our research is focused on reliable and efficient methods for the automatic interpretation of non-rigid three-dimensional shapes. In particular, we have been working on novel approaches to **Shape Matching** and on the design of **Feature Descriptors**.
  
- +== Matching ==
- +
-===== Matching ===== +
- +
-<html> +
-<iframe width="425" height="349" src="http://www.youtube.com/embed/ktKenG_CazE?hl=en&fs=1" frameborder="0" allowfullscreen></iframe> +
-</html>+
  
 The goal of shape matching is to register corresponding surface regions of two given three-dimensional shapes. This means for example to identify the hands, the feet and the head of two human figures. Once two shapes are registered, one can infer morphs between them. The **video** shows examples of such morphs, e.g. interpolating  between a samba dancer and a hip hop dancer. In each of these example sequences, a registration of the first and the last shape has been computed, all intermediate frames are obtained by linear interpolation. The goal of shape matching is to register corresponding surface regions of two given three-dimensional shapes. This means for example to identify the hands, the feet and the head of two human figures. Once two shapes are registered, one can infer morphs between them. The **video** shows examples of such morphs, e.g. interpolating  between a samba dancer and a hip hop dancer. In each of these example sequences, a registration of the first and the last shape has been computed, all intermediate frames are obtained by linear interpolation.
Line 25: Line 17:
  
  
- +== Feature Descriptors ==
- +
-===== Feature Descriptors =====+
  
 {{:research:topics:shape_analysis:feature_descriptor.png?200}} {{:research:topics:shape_analysis:feature_descriptor.png?200}}
Line 35: Line 25:
 In our research we aim at feature descriptors which are robust to shape articulations while capturing as much information as possible. A very powerful mathematical tool for this task is the eigendecomposition of the Laplace--Beltrami operator. In our research we aim at feature descriptors which are robust to shape articulations while capturing as much information as possible. A very powerful mathematical tool for this task is the eigendecomposition of the Laplace--Beltrami operator.
  
-----+==== Contact ==== 
 + 
 +<memberlist> 
 +<dokuwiki> 
 +<filter> 
 +<grps>^shape$</grps> 
 +</filter> 
 +<user>^cremers$</user> 
 +</dokuwiki> 
 +</memberlist>
  
-====== Related publications ======+==== Related publications ====
 <bibtex> <bibtex>
-<topic>Shape Analysis</topic>+<keywords>shape</keywords> 
 +<bytype>-1</bytype>
 </bibtex> </bibtex>
  

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More