Abstract
In recent years, the Internet of vehicles (IOV) with intelligent networked automobiles as terminal node has gradually become the development trend of automotive industry and research hot spot in related fields. This is due to its characteristics of intelligence, networking, low-carbon and energy saving. Real time emotion recognition for drivers and pedestrians in the community can be utilized to prevent fatigue driving and malicious collision, keep safety verification and pedestrian safety detection. This paper mainly studies the face emotion recognition model that can be utilized for IOV. Considering the fluctuation of image acquisition perspective and image quality in the application scene of IOV, the natural scene video similar to vehicle environment and its galvanic skin response (GSR) are utilized to make the testing set of emotion recognition. Then an expression recognition model combining codec and Support Vector Machine classifier is proposed. Finally, emotion recognition testing is completed on the basis of Algorithm 1. The matching accuracy between the emotion recognition model and GSR is 82.01%. In the process of model testing, 189 effective videos are involved and 155 are correctly identified.
Highlights
With the development and integration of information technology, computer technology and automobile manufacturing industry, the Internet of vehicles (IOV) proposed to improve the level of automobile intelligent driving is known to public
IOV is a branch of industrial Internet of things (IOT) technology, so it has the advantages of sensing technology, mobile communication technology and intelligent analysis of the IOT [1]
This paper focuses on face emotion recognition technology which can be applied to vehicle environment in community public space
Summary
With the development and integration of information technology, computer technology and automobile manufacturing industry, the IOV proposed to improve the level of automobile intelligent driving is known to public. IOV is the specific implementation and application of traditional Internet of things technology in automotive field It can greatly improve the intelligence and efficiency of traffic management by wireless communication technology and intelligent information processing technology. Emotion recognition technology has high research value in the field of IOV real-time monitoring applied to fatigue driving, safety verification, malicious collision and pedestrian safety detection [4]. Emotion recognition is different from automobile manufacturing, the latter is the product of second industrial revolution with a long development process. It has become a hot research field with its excellent performance and application value [5]. The video emotion recognition process was mainly divided into three processes, the definition of video emotional label, the training of video expression recognition models and the recognition of video emotion
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