Quantitative Assessment Of Facial Paralysis Based On Content And Spatiotemporal Features

Facial paralysis is a common clinical condition with the rate from 20 to 25 patients per 100,000 people per year.This disease is usually caused by nerve damage,serious sequelae may remain if not treated properly and early.A way to quantitatively evaluate the degrees of condition to apply treatment methods is very helpful.In view of this requirement,this paper uses facial expression data to extract more accurate information,which provides guidance for doctors to more objectively identify facial paralysis in patients with facial paralysis.The main research results are as follows:(1)Aiming at the shortcomings of the traditional method on the asymmetry of the static image by positioning,illumination,shadow and the existence of itself,on one hand we propose a method based on the combination of LBP and Gabor filter(LBP +Gabor)to extract the asymmetric and motion features.Using rotation invariance and gray scale invariance of LBP reduce the influence of light,and then use Gabor filter to reduce the noise and redundancy information in the LBP image.On the other hand,for the nonuniformity of the passband in the Gabor filter,this paper proposes a feature extraction method based on the CMF(Concentric Modulation Filter)method,and combines LBP and CMF(LBP + CMF).The passband of CMF is the same in all directions,which can extract more accurate features.Experiments show that the application of LBP method have better effectiveness and practicality than traditional method(Gabor and CMF).(2)The uncorrelated factors in the static images(such as the teeth in the mouth,the shadow and the mole of the mouth)affect the precise of features extraction.To solve this problem,the method of target tracking is applied to exact feature.First,in the first frame of the face image,spatiotemporal features is extracted by the marker tracking in the image sequence.We use KLT(Kanade-Lucas-Tomasi)and Mean-Shift two methods to prove the extraction of spatiotemporal characteristics of the identification of validity.(3)The synchronization of the start and the end time point and speed normalization for different patient expression,solve the different patients face the implementation of the problem of asynchronous.Multidimensional data experiments show that the time-space feature is extracted and synchronized and normalized,and the correct rate of surface paralysis is better than that of content-based method,which is better for doctors.At the same time,the methods proposed in this paper extend the theoretical basis of quantitative assessment of facial paralysis.The results of the experiment is helpful for the clinicians to make a reasonable condition to judge and treatment for patients.