title: Dynamic Cascades with Bidirectional Bootstrapping for Action Unit Detection in Spontaneous Facial Behavior.
abstract: Automatic facial action unit detection from video is a long-standing problem in facial expression analysis. Research has focused on registration, choice of features, and classifiers. A relatively neglected problem is the choice of training images. Nearly all previous work uses one or the other of two standard approaches. One approach assigns peak frames to the positive class and frames associated with other actions to the negative class. This approach maximizes differences between positive and negative classes, but results in a large imbalance between them, especially for infrequent AUs. The other approach reduces imbalance in class membership by including all target frames from onsets to offsets in the positive class. However, because frames near onsets and offsets often differ little from those that precede them, this approach can dramatically increase false positives. We propose a novel alternative, dynamic cascades with bidirectional bootstrapping (DCBB), to select training samples. Using an iterative approach, DCBB optimally selects positive and negative samples in the training data. Using Cascade Adaboost as basic classifier, DCBB exploits the advantages of feature selection, efficiency, and robustness of Cascade Adaboost. To provide a real-world test, we used the RU-FACS (a.k.a. M3) database of nonposed behavior recorded during interviews. For most tested action units, DCBB improved AU detection relative to alternative approaches.
authors.affiliation: Image Engineering Laboratory, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Yunfeng
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: Robotics Institute, Carnegie Mellon University, 211 Smith Hall, 5000 Forbes Ave., Pittsburg, PA 15213.
authors.forename: Fernando
authors.initials: F
authors.lastname: De la Torre
authors.affiliation: Department of Psychology, University of Pittsburgh and the Robotics Institute, Carnegie Mellon University, 4327 Sennott Square, Pittsburgh, PA 15260.
authors.forename: Jeffrey F
authors.initials: JF
authors.lastname: Cohn
authors.affiliation: Image Engineering Laboratory, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Yu-Jin
authors.initials: YJ
authors.lastname: Zhang
keywords: FACS; Facial expression analysis; action unit detection; bidirectional bootstrapping; dynamic cascade boosting