Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space

Abstract

Our goal is to automatically determine the cast of a feature-length film. This is challenging because the cast size is not known, with appearance changes of faces caused by extrinsic imaging factors (illumination, pose, expression) often greater than due to differing identities. The main contribution of this paper is an algorithm for clustering over face appearance manifolds. Specifically: (i) we develop a novel algorithm for exploiting coherence of dissimilarities between manifolds, (ii) we show how to estimate the optimal dataset-specific discriminant manifold starting from a generic one, and (iii) we describe a fully automatic, practical system based on the proposed algorithm. The performance of the system is evaluated on well-known featurelength films and situation comedies on which it is shown to produce good results.

Cite

Text

Arandjelovic and Cipolla. "Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006. doi:10.1109/CVPR.2006.64

Markdown

[Arandjelovic and Cipolla. "Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006.](https://mlanthology.org/cvpr/2006/arandjelovic2006cvpr-automatic/) doi:10.1109/CVPR.2006.64

BibTeX

@inproceedings{arandjelovic2006cvpr-automatic,
  title     = {{Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space}},
  author    = {Arandjelovic, Ognjen and Cipolla, Roberto},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2006},
  pages     = {1513-1520},
  doi       = {10.1109/CVPR.2006.64},
  url       = {https://mlanthology.org/cvpr/2006/arandjelovic2006cvpr-automatic/}
}