Optimization Of 3D Fitting Model Parameters Based On Mobile User Experience

With the maturity of 5th generation mobile networks(5G)technology,Virtual Reality(VR)development environment has been greatly improved that the application of VR technology will also be more extensive and mature.As one of the applications of VR technology in the field of clothing marketing,3D fitting is worthy of attention and research.Judging from the development status of 3D fitting,at present,3D fitting is not only available on Taobao,but also has more independent professional platforms for 3D fitting.However,few people have heard of it.Through existing research and investigation,it is found that the main reason is that the reality of the current 3D fitting models is not ideal.Although there are various methods for improving the effects of 3D models in related studies,the methods can only be implemented on the basis of professional equipment,professionals,and professional operations.It is difficult to quickly commercialize 3D fitting in the current environment.In order to promote the development of 3D fitting as soon as VR technology has not yet been fully applied,this study starts from the human parameters of 3D models and optimizes parameters from the perspective of user experience.A low-cost,easy-to-implement 3D fitting improvement method is proposed.Firstly,the key parameter set of the 3D fitting model studied in this paper is established by set theory.Relevant parameters for 3D fitting are obtained by combing the literature,constructing parameter set A,obtaining the fitting parameters deemed important by users through questionnaires,constructing parameter set B,filtering out unnecessary parameters through expert interviews,and constructing parameter set C.Through the set operation F = A?B-C,the key parameter set F of the 3D fitting is studied.Based on the user experience cellular model and technology acceptance theory,the parameter length parameters,dimensional parameters,and overall parameters are laid down from the perspective of ease of use for the later research.Secondly,the 3D fitting experience experiment and the questionnaire survey method are used to get the order of importance of the parameters.After considering the platform parameters including completeness,entry method,and operation stability,etc.,the "good box" was finally selected as the fitting platform for this experiment.After the 3D fitting experimenter was organized to conduct experiments,the importance of the parameters was determined.Fill in the evaluation scale and analyze the statistical results by grey correlation analysis to obtain the parameter ranking results.Based on the ranking of the parameters and the coefficient of variation,etc.,a preliminary conclusion is drawn.Finally,a personalized input mode for 3D fitting parameters is established based on user classification and utility threshold.The utility function is used to fit the effect of the 3D fitting model,and the triangular fuzzy number is used to solve the utility coefficient of the parameter to obtain the expression.The users are divided into nine categories according to the dimensions of "willing to spend time" and "high or low requirements for the authenticity of the model".Due to the mutual influence of the two factors,they are finally integrated into seven categories of users according to the high and low requirements for utility.The parameters are added one by one according to the order of weight.In order to reflect the dominance of the user,after the user has established the model,he can also choose whether to be satisfied or not.If he is not satisfied,he will jump directly to the next level of parameters and further add parameters to ultimately achieve a personalized service model that the user is satisfied with.