LUO Changwei, LI Rui, YU Lingyun, YU Jun, WANG Zengfu. Automatic Tongue Tracking in X-Ray Images[J]. Chinese Journal of Electronics, 2015, 24(4): 767-771. doi: 10.1049/cje.2015.10.017
Citation: LUO Changwei, LI Rui, YU Lingyun, YU Jun, WANG Zengfu. Automatic Tongue Tracking in X-Ray Images[J]. Chinese Journal of Electronics, 2015, 24(4): 767-771. doi: 10.1049/cje.2015.10.017

Automatic Tongue Tracking in X-Ray Images

doi: 10.1049/cje.2015.10.017
Funds:  This work is supported by the Open Project Program of the State Key Lab of CAD&CG, Zhejiang University (No.A1501), and the National Natural Science Foundation of China (No.61303150, No.61472393).
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  • Corresponding author: YU Jun (corresponding author) wasborn in 1983. He is a research associate professorof University of Science and Technologyof China. His research interests includehuman computer interaction and intelligentrobot. (Email: harryjun@ustc.edu.cn)
  • Received Date: 2015-03-09
  • Rev Recd Date: 2015-06-14
  • Publish Date: 2015-10-10
  • X-ray imaging is an effective technique to obtain the continuous motions of the vocal tract during speech, and Active appearance model (AAM) is a useful tool to analyze the X-ray images. However, for the task of tongue tracking in X-ray images, the accuracy of AAM fitting is insufficient. AAM aims to minimize the residual error between the model appearance and the input image. It often fails to accurately converge to the true landmarks. To improve the tracking accuracy, we propose a fitting method by combining Constrained local model (CLM) into AAM. In our method, we first combine the objective functions of AAM and CLM into a single objective function. Then, we project out the texture variation and derive a gradient based method to optimize the objective function. Our method effectively incorporates not only the shape prior and global texture, but also local texture around each landmark. Experiments demonstrate that the proposed method significantly reduces the fitting error. We also show that realistic 3D tongue animation can be created by using tongue tracking results of the X-ray images.
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