Automatic 3D face landmark localization based on 3D vector field analysis

In applications such as 3D face synthesis and animation, a prominent face landmark is required to enable 3D face normalization, pose correction, 3D face recognition and reconstruction. Due to variations in facial expressions, automatic 3D face landmark localization remains a challenge. Nose tip is one of the salient landmarks in a human face. In this paper, a novel nose tip localization technique is proposed. In the proposed approach, the rotation of the 3D vector field is analyzed for robust and efficient nose tip localization. The proposed technique has the following three characteristics: (1) it does not require any training; (2) it does not rely on any particular model; (3) it is very efficient, requiring an average time of only 1.9s for nose tip detection. We tested the proposed technique on BU3DFE and Shrec'10 datasets. Experimental results show that the proposed technique is robust to variations in facial expressions, achieving a 100% detection rate on these publicly available 3D face datasets.

[1]  Mohammed Bennamoun,et al.  A novel algorithm for efficient depth segmentation using low resolution (Kinect) images , 2015, 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA).

[2]  Abdul Bais,et al.  Quantification and visualization of MRI cartilage of the knee: A simplified approach , 2010, 2010 6th International Conference on Emerging Technologies (ICET).

[3]  Wang Kongqiao,et al.  Local binary pattern probability model based facial feature localization , 2010, 2010 IEEE International Conference on Image Processing.

[4]  S. Panchanathan,et al.  A hybrid technique for facial feature point detection , 2002, Proceedings Fifth IEEE Southwest Symposium on Image Analysis and Interpretation.

[5]  Raimondo Schettini,et al.  3D face detection using curvature analysis , 2006, Pattern Recognit..

[6]  Mohammed Bennamoun,et al.  Performance Evaluation of 3D Local Surface Descriptors for Low and High Resolution Range Image Registration , 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

[7]  Tieniu Tan,et al.  Robust nose detection in 3D facial data using local characteristics , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[8]  Mohammed Bennamoun,et al.  3D-Div: A novel local surface descriptor for feature matching and pairwise range image registration , 2013, 2013 IEEE International Conference on Image Processing.

[9]  M. Bennamoun,et al.  Automatic object detection using objectness measure , 2013, 2013 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA).

[10]  Jun Wang,et al.  A 3D facial expression database for facial behavior research , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[11]  Lijun Yin,et al.  Automatic pose estimation of 3D facial models , 2008, 2008 19th International Conference on Pattern Recognition.

[12]  Xiaobo Ren,et al.  Robust Nose Detection and Tracking Using GentleBoost and Improved Lucas-Kanade Optical Flow Algorithms , 2007, ICIC.

[13]  Mohammed Bennamoun,et al.  A novel 3D vorticity based approach for automatic registration of low resolution range images , 2015, Pattern Recognit..

[14]  Mohammed Bennamoun,et al.  Iterative deep learning for image set based face and object recognition , 2016, Neurocomputing.

[15]  Patrick J. Flynn,et al.  Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Rana Fareed Ghani,et al.  Nose Tip Detection Using Shape index and Energy Effective for 3 d Face Recognition , 2013 .

[17]  B. Achiriloaie,et al.  VI REFERENCES , 1961 .

[18]  Mohammed Bennamoun,et al.  A Novel Local Surface Description for Automatic 3D Object Recognition in Low Resolution Cluttered Scenes , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[19]  Mohammed Bennamoun,et al.  A training-free nose tip detection method from face range images , 2011, Pattern Recognit..

[20]  Chun Chen,et al.  Robust 3D Face Landmark Localization Based on Local Coordinate Coding , 2014, IEEE Transactions on Image Processing.