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Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry

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Volumetric descriptions of objects from multiple views.

W N Martin¹, J K Aggarwal

¹MEMBER, IEEE, Laboratory for Image and Signal Analysis, University of Texas, Austin, TX 78712; Department of Applied Mathematics and Computer Sciences, University of Virginia, Char.

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 27, 2011

Summary

This summary is machine-generated.

This study introduces a novel "volume segment" representation for creating and refining bounding volumes from object contours. This method aids in approximating object shapes from image sequences using viewpoint data.

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Area of Science:

Computer Vision
Geometric Modeling
3D Reconstruction

Background:

Object approximation from image sequences is crucial for various applications.
Existing volumetric representations may lack efficiency in modification or surface detail.

Purpose of the Study:

To present a novel "volume segment" representation for object approximation.
To enable efficient creation and refinement of bounding volumes from image contours.

Main Methods:

Utilizing occluding contours from image sequences with specified viewpoints.
Developing a volumetric representation that balances modifiability and surface detail description.

Main Results:

The proposed "volume segment" representation facilitates the approximation of bounding volumes.
This representation supports both initial creation and continuous refinement of object approximations.

Conclusions:

The "volume segment" representation is an effective approach for approximating objects from contours.
This method offers a suitable volumetric representation for detailed and modifiable object modeling.