Fusion of audio and visual cues for laughter detection
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Audiovisual laughter detection based on temporal features
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Face recognition across pose: A review
Pattern Recognition
Static vs. dynamic modeling of human nonverbal behavior from multiple cues and modalities
Proceedings of the 2009 international conference on Multimodal interfaces
Is this joke really funny? judging the mirth by audiovisual laughter analysis
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Computer Vision and Image Understanding
Pre-organizing Shape Instances for Landmark-Based Shape Correspondence
International Journal of Computer Vision
Comparison of prediction-based fusion and feature-level fusion across different learning models
Proceedings of the 20th ACM international conference on Multimedia
Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition
International Journal of Computer Vision and Image Processing
Image and Vision Computing
Bimodal log-linear regression for fusion of audio and visual features
Proceedings of the 21st ACM international conference on Multimedia
Audiovisual three-level fusion for continuous estimation of Russell's emotion circumplex
Proceedings of the 3rd ACM international workshop on Audio/visual emotion challenge
Rough set based pose invariant face recognition with mug shot images
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper proposes novel ways to deal with pose variations in a 2-D face recognition scenario. Using a training set of sparse face meshes, we built a point distribution model and identified the parameters which are responsible for controlling the apparent changes in shape due to turning and nodding the head, namely the pose parameters. Based on them, we propose two approaches for pose correction: 1) a method in which the pose parameters from both meshes are set to typical values of frontal faces, and 2) a method in which one mesh adopts the pose parameters of the other one. Finally, we obtain pose corrected meshes and, taking advantage of facial symmetry, virtual views are synthesized via Thin Plate Splines-based warping. Given that the corrected images are not embedded into a constant reference frame, holistic methods are not suitable for feature extraction. Instead, the virtual faces are fed into a system that makes use of Gabor filtering for recognition. Unlike other approaches that warp faces onto a mean shape, we show that if only pose parameters are modified, client specific information remains in the warped image and discrimination between subjects is more reliable. Statistical analysis of the authentication results obtained on the XM2VTS database confirm the hypothesis. Also, the CMU PIE database is used to assess the performance of the proposed methods in an identification scenario where large pose variations are present, achieving state-of-the-art results and outperforming both research and commercial techniques.