Research on Recognition Technology of Amur Tiger Gait Features Based on Video

Abstract With the continuous advancement of technology, people are paying more and more attention to the living environment of wild animals. Located at the top of the food chain of the forest ecosystem, the Siberian tiger is a flagship species and umbrella species for biodiversity protection. The effective protection and sustainable survival of its population has far-reaching natural and social significance for China’s ecological security1. At present, the research on the Siberian tiger is mainly concentrated in the biological fields such as genes and heredity. Only a small amount of research on the detection of Siberian tigers and their footprints in static images. Research on the behavior recognition of Siberian tigers in videos is currently in its infancy. In the field of computer vision, as an independent research object, more and more researchers pay attention to the automatic recognition of gait. Based on the human gait model, a standard database for evaluating the performance of gait recognition algorithms has been established to promote the research of gait recognition. development of. This article will use deep neural convolutional networks and feature subspace learning algorithms to extract the gait features of the Siberian tiger from video images and establish a gait model of the Siberian tiger. This will lay the foundation for the identification of Siberian tigers and further research on their health status, and provide a foundation for the wild Provide theoretical support for animal protection.