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Computer Vision and Image Understanding
Article . 2001 . Peer-reviewed
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Generating Realistic Facial Expressions with Wrinkles for Model-Based Coding

Generating realistic facial expressions with wrinkles for model-based coding
Authors: Yin, Lijun; Basu, Anup;

Generating Realistic Facial Expressions with Wrinkles for Model-Based Coding

Abstract

Summary: Due to the limitations of current computer graphics technology mimicing realistic facial textures, such as wrinkles, is very difficult. Facial texture updating and compression are crucial to achieving realistic facial animation for low bit rate modelbased coding. In this paper, we present a partial texture updating method for realistic facial expression synthesis with facial wrinkles. First, fiducial points on a face are estimated using a color-based deformable template matching method. Second, an extended dynamic mesh matching algorithm is developed for face tracking. Next, Textures Of Interest (TOI) in the potential expressive wrinkles and mouth-eye texture areas are captured by the detected fiducial points. Among the TOI, the so-called active textures or expressive textures are extracted by exploring temporal correlation information. Finally, the entire facial texture is synthesized using the active texture. Compared to the entire texture updating scheme, partially updating and compressing facial textures significantly reduce the computational complexity and bit rates while still producing an acceptable visual quality. Experiments on the video sequences demonstrate the advantage of the proposed algorithm.

Related Organizations
Keywords

texture coding, Pattern recognition, speech recognition, model-based coding, feature detection, [INFO] Computer Science [cs], Computing methodologies for image processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Average
Top 10%
Top 10%
Green