Research On Image Positioning Decision-making Based On The Neural Mechanism Of Visual Cognition

With the official release of the full text of the 14 th five-year plan of the People's Republic of China for national economic and social development and the outline of long-term goals for 2035(hereinafter referred to as the "plan"),industrial design innovation has ushered in new development.In the plan,it is emphasized to focus on improving the industrial innovation ability and accelerate the development of R ? D design,industrial design and other services.The innovative design of products has become an important role in reflecting the innovation ability of China's manufacturing industry and an important foundation for industrial upgrading and development.In today's era of perceptual consumption,it has become the focus of enterprises to provide competitive innovative design products.In the innovative design of products,the most intuitive expression is the innovation of product modelling design.Product modelling has become the main source of attracting consumers and has become a key factor affecting the comprehensive value of products.For the traditional innovative design of product modelling,designers mainly design through their own experience and subjective feelings or obtain the quantitative results of consumer experience to carry out the perceptual design.However,due to individual differences,designers and consumers of different identities of knowledge,experience and social background,the evaluation results are biased,resulting in emotional design can not meet the expected requirements.The most important key in perceptual design is to obtain the image needs of users.As an important embodiment of meeting the high-level spiritual needs of users,the image has been widely valued and concerned in the process of design innovation.With the development of Kansei Engineering,implicit measurement methods commonly used in psychology have been applied to the first stage of the design innovation process,that is,to obtain the image needs of users for products.Researches in neuroscience,cognitive science and other disciplines show that implicit measurement methods such as eye movement test,EEG test and implicit association test can obtain users' real and objective behavioural and psychological feelings.Therefore,in order to obtain accurate image information of users,this paper combines perceptual engineering with eye movement test,EEG test and implicit association test,and combines the physiological and psychological evaluation indexes of users,and proposes an image location decision method based on visual cognitive neural mechanism.The subject is studied from three aspects: the acquisition of perceptual information of group cognition,the establishment of product selection and classification model,and the image positioning decision under the neural mechanism of visual cognition.Firstly,through the acquisition of group cognitive-perceptual information,the original sample library of products is established,and the cognitive evaluation of samples is carried out,and the image semantic set is established;secondly,according to the sample library and image set obtained from group cognitive-perceptual information,the positive perceptual concept of samples is proposed,and the subjects are trained to master the positive perceptual concept,and the product classification knowledge based on joint eye movement EEG is implemented In the experiment,the cognitive data is analyzed to obtain the feature data,and the machine learning algorithm is applied to classify to obtain the positive perceptual sample library;finally,the positive perceptual sample library obtained from the product selection classification model is evaluated by five points of semantics to obtain the semantic-based classification sample library,and the three-point semantic evaluation is implemented to filter out the inconsistent samples between the semantic classification and the three-point semantic evaluation Symbolic samples with clear semantics can reduce the influence of subjective factors in the process of model construction.Image semantic cognitive experiment based on implicit measurement method is carried out on symbolic samples,and image decision-making model based on the visual cognitive neural mechanism is constructed.Non-symbolic samples are used to verify the reliability and effectiveness of the model.The feasibility of the method is verified by taking the consumer UAV of advanced equipment products in Guizhou's top thousand billion industries as an example.The results show that the proposed image decision-making model based on the visual cognitive neural mechanism can achieve the evaluation effect similar to the subjective evaluation,and through the evaluation of the expert group,the deviation of the results is smaller.The proposed method can obtain objective image data and provide better design decisions for designers.