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individual automatic detection and identification of big cats with the combination of different body parts

Integrative Zoology 2023年第1期18卷 157-168页

作者： Chunmei SHI Jing XU Nathan James ROBERTS Dan LIU Guangshun JIANG College of Mathematics and Computer Science Zhejiang Agriculture and Forestry UniversityHangzhouChina Department of Mathematics School of ScienceNortheast Forestry UniversityHarbinChina Feline Research Center National Forestry and Grassland AdministrationCollege of Wildlife and Protected AreasNortheast Forestry UniversityHarbinChina Siberian Tiger Park HarbinChina

The development of facial recognition technology has become an increasingly powerful tool in wild animal indi-vidual *** this paper,we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network(CNN).We collected dataset including 12244 images from 47 individual Amur tigers(Panthera tigris altaica)at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard(Panthera pardus orientalis)by infrared ***,the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each *** the different feature regions of the image,like face stripe or spots,CNNs and multi-layer perceptron models were applied to automatically identify tiger and leopard individuals,*** results show that the identiﬁcation accuracy of Amur tiger can reach up to 93.27%for face front,93.33%for right body stripe,and 93.46%for left body ***,the combination of right face,left body stripe,and right body stripe achieves the highest accuracy rate,up to 95.55%.Consequently,the combination of different body parts can improve the individual identiﬁcation ***,it is not the higher the number of body parts,the higher the accuracy *** combination model with 3 body parts has the highest *** identiﬁcation accuracy of Amur leopard can reach up to 86.90%for face front,89.13%for left body spots,and 88.33%for right body *** accuracy of different body parts combination is lower than the independent *** wild Amur leopard,the combination of face with body spot part is not helpful for the improvement of identiﬁcation *** most effective identiﬁcation part is still the independent left or right body spot *** can be applied in long-term monitoring of big cats,including big data analysis for animal behavior,and be helpful

关键词： combination of body parts individual automatic identiﬁcation object detection Panthera pardus orientalis Panthera tigris altaica

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