Active shape models—their training and application
Computer Vision and Image Understanding
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Robust Active Shape Model Search
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A Non-Linear Gray-Level Appearance Model Improves Active Shape Model Segmentation
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Deformable templates for face recognition
Journal of Cognitive Neuroscience
Facial feature localization based on an improved active shape model
Information Sciences: an International Journal
Gabor feature constrained statistical model for efficient landmark localization and face recognition
Pattern Recognition Letters
A robust face detection scheme for surveillance applications
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
Robust modified active shape model for automatic facial landmark annotation of frontal faces
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Novel Gaussianized vector representation for improved natural scene categorization
Pattern Recognition Letters
Constraint shape model using edge constraint and Gabor wavelet based search
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Pattern Recognition Letters
| Hi-index | 0.01 |
In this paper, we present several improvements on the conventional Active Shape Models (ASM) for face alignment. Despite the accuracy and robustness of the ASMs in the image alignment, its performance depends heavily on the initial parameters of the shape model, aswell as the local texture model for each landmark and the corresponding local matching strategy. In this work, to improve the ASMs for face alignment, several measures are taken. First, salient facial features, such as the eyes and the mouth, are localized based on a face detector. These salient features are then utilized to initialize the shape model and provide region constraints on the subsequent iterative shape searching. Secondly, we exploit the edge information to construct better local texture models for the landmarks on the face contour. The edge intensity at the contour landmark is used as a self-adaptive weight when calculating the Mahalanobis distance between the candidate profile and the reference one. Thirdly, to avoid their unreasonable shift from the pre-Iocalized salient features, landmarks around the salient features are adjusted before applying the global subs pace constraints. Experiments on a database containing 300 labeled face images show that the proposed method performs significantly better than traditional ASMs.