Feature-based techniques for real-time morphable model facial image analysis

Siddhartha Chaudhuri; Randhir Kumar Singh; Edoardo Charbon

doi:10.1117/12.587980

14 March 2005 Feature-based techniques for real-time morphable model facial image analysis

Siddhartha Chaudhuri, Randhir Kumar Singh, Edoardo Charbon

Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005) https://doi.org/10.1117/12.587980
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

We present an algorithm to quickly analyse and compress facial images using a 2-dimensional morphable model. It runs in real-time on reasonable resources, and offers considerable opportunities for parallelization. A morphable model associates a "shape vector" and a "texture vector" with each image of a sample set. The model is used to analyze a novel image by estimating the model parameters via an optimization procedure. The novel image is compressed by representing it by the set of best match parameters. For real-time performance, we separate the novel image into shape and texture components by computing correspondences between the novel image and a reference image, and match each component separately using eigenspace projection. This approach can be easily parallelized. We improve the speed of algorithm by exploiting the fact that facial correspondence fields are smooth. By computing correspondences only at a number of "feature points" and using interpolation to approximate the dense fields, we drastically reduce the dimensionality of the vectors in the eigenspace, resulting in much smaller compression times. As an added benefit, this system reduces spurious correspondences, since weak features that may confuse the correspondence algorithm are not tracked.

Citation Download Citation

Siddhartha Chaudhuri, Randhir Kumar Singh, and Edoardo Charbon "Feature-based techniques for real-time morphable model facial image analysis", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); https://doi.org/10.1117/12.587980

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KEYWORDS

Image compression

Image analysis

Statistical modeling

Principal component analysis

3D modeling

Databases

Optical flow

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