Live Recognition and Application based on Video technology under Complex Disaster Conditions
Author:Ying Xu, Chunxue Wu, Xiao Lin Author Unit: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China The Department of Computer Science, Shanghai Normal University, Shanghai, China
Abstract：Living body recognition is a hot topic in the field of video recognition research. The research on biometrics such as face recognition, fingerprint recognition, iris recognition, etc. has been widely used in many fields such as education systems, business systems, management systems and so on. In the aspects of virtual reality, video games, intelligent monitoring, etc., motion recognition and gesture recognition technology are involved. Motion recognition can be achieved through sensors and recognition algorithms. The SVM kernel function algorithm has a higher problem in linear and nonlinear high-dimensional feature spaces. The ability of classification and recognition. The factors that distinguish living bodies can start with the target movement, shape, color, and heart rate in the video. The most important thing is that the living heart rate has regular and periodic changes. Collecting heart rate signals, fine analysis of heart rate signals can distinguish the living body type and the living body specific Identity. The research on living body recognition based on video technology under complex disaster conditions is of great significance. This paper designs a living body detection prototype system DHP based on video technology under complex disaster conditions. Experimental results show that the accuracy of the proposed method is 97.6％, which is higher than the previous recognition methods. In this article, in each video under complex disaster conditions, a set of prototype system strategies are adopted to locate the living target progressively and obtain the characteristics of the live heart rate signal in each video. The information distinguishes living body categories. Definition 0 represents living body and 1 represents non-living body.
Keywords：Dynamic recognition;Heart rate vital sign information recognition, Gesture recognition; Support vector machine;SVM kernel function.
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