Greedy search for descriptive spatial face features

Caner Gacav; Burak Benligiray; Cihan Topal

ICASSP 2017accepted0 citations

Greedy search for descriptive spatial face features

Caner Gacav, Burak Benligiray, Cihan Topal

Abstract

Facial expression recognition methods use a combination of geometric and appearance-based features. Spatial features are derived from displacements of facial landmarks, and carry geometric information. These features are either selected based on prior knowledge, or dimension-reduced from a large pool. In this study, we produce a large number of potential spatial features using two combinations of facial landmarks. Among these, we search for a descriptive subset of features using sequential forward selection. The chosen feature subset is used to classify facial expressions in the extended Cohn-Kanade dataset (CK+), and delivered 88.7% recognition accuracy without using any appearance-based features.

BibTeX

@inproceedings{icassp2017_greedysearchford,
  title = {Greedy search for descriptive spatial face features},
  author = {Caner Gacav and Burak Benligiray and Cihan Topal},
  booktitle = {ICASSP 2017},
  year = {2017}
}