Name
Abstract | ||
|---|---|---|
Aligning faces with non-rigid muscle motion in the real-world streaming video is a challenging problem. We propose a novel automatic video-based face registration architecture for facial expression recognition. The registration process is formulated as a dense SIFT-flow-and optical-flow-based affine warping problem. We start off by estimating the transformation of an arbitrary face to a generic reference face with canonical pose. This initialization in our framework establishes a head pose and person independent face model. The affine transformation computed from the initialization is then propagated by affine transformation estimated from the dense optical flow to guarantee the temporal smoothness of the nonrigid facial appearance. We call this method SIFT and optical flow affine image transform (SOFAIT). This real-time algorithm is designed for realistic streaming data, allowing us to analyze the facial muscle dynamics in a meaningful manner. Visual and quantitative results demonstrate that the proposed automatic video-based face registration technique captures the appearance changes in spontaneous expressions and outperforms the state-of-the-art technique. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/FG.2013.6553790 | 2013 10TH IEEE INTERNATIONAL CONFERENCE AND WORKSHOPS ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG) |
Keywords | Field | DocType |
muscle,face recognition,image registration,affine transformation,optical imaging,estimation,pose estimation,visualization | Affine transformation,Scale-invariant feature transform,Computer vision,Facial recognition system,Image warping,Pose,Artificial intelligence,Initialization,Optical flow,Mathematics,Image registration | Conference |
ISSN | Citations | PageRank |
2326-5396 | 3 | 0.37 |
References | Authors | |
20 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Songfan Yang | 1 | 343 | 17.48 |
| Le An | 2 | 217 | 11.24 |
| Bir Bhanu | 3 | 3356 | 380.19 |
| Ninad Thakoor | 4 | 94 | 13.39 |