EMPATH: face, emotion, and gender recognition using holons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synthesizing realistic facial expressions from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Bayesian robustification for audio visual fusion
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Motion Estimation in Model-Based Facial Image Coding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human expression recognition from motion using a radial basis function network architecture
IEEE Transactions on Neural Networks
Dynamic face recognition: From human to machine vision
Image and Vision Computing
Recognition of human faces: from biological to artificial vision
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Spiral topologies for biometric recognition
ASB'03 Proceedings of the 1st international conference on Advanced Studies in Biometrics
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We present ongoing work on a project for automatic recognition of spontaneous facial actions (FACs). Current methods for automatic facial expression recognition assume images are collected in controlled environments in which the subjects deliberately face the camera. Since people often nod or turn their heads, automatic recognition of spontaneous facial behavior requires methods for handling out-of-image-plane head rotations. There are many promising approaches to address the problem of out-of-image plane rotations. In this paper we explore an approach based on 3-D warping of images into canonical views. Since our goal is to explore the potential of this approach, we first tried with images with 8 hand-labeled facial landmarks. However the approach can be generalized in a straight-forward manner to work automatically based on the output of automatic feature detectors. A front-end system was developed that jointly estimates camera parameters, head geometry and 3-D head pose across entire sequences of video images. Head geometry and image parameters were assumed constant across images and 3-D head pose is allowed to vary. First a a small set of images was used to estimate camera parameters and 3D face geometry. Markov chain Monte-Carlo methods were then used to recover the most-likely sequence of 3D poses given a sequence of video images. Once the 3D pose was known, we warped each image into frontal views with a canonical face geometry. We evaluate the performance of the approach as a front-end for an spontaneous expression recognition task.