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Fully automatic recognition of the temporal phases of facial actions (2012)
| Content Provider | CiteSeerX |
|---|---|
| Author | Valstar, Michel F. Pantic, Maja |
| Abstract | Abstract—Past work on automatic analysis of facial expressions has focused mostly on detecting prototypic expressions of basic emotions like happiness and anger. The method proposed here enables the detection of a much larger range of facial behavior by recognizing facial muscle actions [action units (AUs)] that compound expressions. AUs are agnostic, leaving the inference about conveyed intent to higher order decision making (e.g., emotion recognition). The proposed fully automatic method not only allows the recognition of 22 AUs but also explicitly models their temporal characteristics (i.e., sequences of temporal segments: neutral, onset, apex, and offset). To do so, it uses a facial point detector based on Gabor-feature-based boosted classifiers to automatically localize 20 facial fiducial points. These points are tracked through a sequence of images using a method called particle filtering with factorized likelihoods. To encode AUs and their temporal activation models based on the tracking data, it applies a combination of GentleBoost, support vector machines, and hidden Markov models. We attain an average AU recognition rate of 95.3 % when tested on a benchmark set of deliberately displayed facial expressions and 72 % when tested on spontaneous expressions. Index Terms—Facial expression analysis, GentleBoost, particle filtering, spatiotemporal facial behavior analysis, support vector machine (SVM). I. |
| File Format | |
| Journal | T-SMC B |
| Language | English |
| Publisher Date | 2012-01-01 |
| Access Restriction | Open |
| Subject Keyword | Temporal Phase Facial Action Automatic Recognition Facial Expression Support Vector Machine Compound Expression Temporal Segment Average Au Recognition Rate Temporal Characteristic Tracking Data Emotion Recognition Facial Point Detector Automatic Analysis Benchmark Set Automatic Method Spatiotemporal Facial Behavior Analysis Spontaneous Expression Basic Emotion Conveyed Intent Facial Fiducial Point Facial Behavior Facial Muscle Action Action Unit Hidden Markov Model Abstract Past Work Order Decision Making Gabor-feature-based Boosted Classifier Prototypic Expression Particle Filtering Index Term Facial Expression Analysis Temporal Activation Model |
| Content Type | Text |
| Resource Type | Article |
