Validation of the automatic tracking for facial landmarks in 3D motion captured images

Aim: The aim of this study was to validate the automatic tracking of facial landmarks in 3D image sequences captured using the Di4D system (Dimensional Imaging Ltd., Glasgow, UK). MATERIALS AND METHODS: 32 subjects (16 males; 16 females) range 18-35 years were recruited. 23 facial landmarks were marked on the face of each subject with a 0.5 mm non-permanent ink. The subjects were asked to perform three facial animations from the rest position (maximal smile, lip purse and cheek puff). Each animation was captured by a 3D stereophotogrammetry video system (Di4D). A single operator digitized landmarks on captured 3D models and the manual digitised landmarks were compared with the automatic tracked landmarks. To investigate the accuracy of manual digitisation, the same operator re-digitized 2 subjects (1 male and 1 female). RESULTS & CONCLUSION: The discrepancies in x, y and z coordinates between the manual digitised landmarks and the automatic tracked facial landmarks were within 0.5 mm and the mean distance between the manual digitisation and the automatic tracking of corresponding landmarks using tracking software was within 0.7 mm which reflects the accuracy of the method( p value was very small). The majority of these distances were within 1 mm. The correlation coefficient between the manual and the automatic tracking of facial landmarks was 0.999 in all x, y, and z coordinates. In conclusion, Automatic tracking of facial landmarks with satisfactory accuracy, would facilitate the analysis of the dynamic motion during facial animations

Innovation in prediction planning for anterior open bite correction

This study applies recent advances in 3D virtual imaging for application in the prediction planning of dentofacial deformities. Stereo-photogrammetry has been used to create virtual and physical models, which are creatively combined in planning the surgical correction of anterior open bite. The application of these novel methods is demonstrated through the surgical correction of a case

Some forecast methods in regression models for categorical time series

We are dealing with the prediction of forthcoming outcomes of a categorical time series. We will assume that the evolution of the time series is driven by a covariate process and by former outcomes and that the covariate process itself obeys and autoregressive law. Two forecasting methods are presented. The first is based on an integral formula for the probabilities of forthcoming events and by a Monte Carlo evaluation of this integral. The second method makes use of an approximation formula for conditional expectations. The procedures proposed are illustrated by an application to data on forest damages. (orig.)Available from TIB Hannover: RR 6137(3) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Innovation in prediction planning for anterior open bite correction

This study applies recent advances in 3D virtual imaging for application in the prediction planning of dentofacial deformities. Stereo-photogrammetry has been used to create virtual and physical models, which are creatively combined in planning the surgical correction of anterior open bite. The application of these novel methods is demonstrated through the surgical correction of a case

On a problem of bases for the regular extension of varieties of algebras

SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman