@inproceedings{327bfab7dc134db09e40dad4a3dd7113,
title = "Behavior classification and image processing for biorobot-rat interaction",
abstract = "In this paper, we focus on rat's behavior classification for biorobot-rat interaction. The automatic behavior analysis and classification of laboratory rats can effectively improve the adaptivity of interaction between rat-like robot and biological rats. Basic image processing algorithm as Labeling and Contour Finding were employed to extract feature parameters (body length, body area, body radius, rotational angle, and ellipticity) of rat's actions. These feature parameters are integrated as the input feature vector of CNN (Convolutional Neural Network) and SVM (Support Vector Machine) training system respectively. Preliminary experiment result shows that the grooming, rotating, crouching and rearing actions could be recognized with extremely high rate (more than 90\%) by both CNN and SVM. Furthermore, CNN provides better recognition rate and SVM provides less computational cost.",
keywords = "CNN, SVM, behavior classification, image processing",
author = "Zirong Wang and Hong Qiao",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2017 ; Conference date: 21-07-2017 Through 23-07-2017",
year = "2017",
month = oct,
day = "19",
doi = "10.1109/ICEIEC.2017.8076631",
language = "英语",
series = "Proceedings of 2017 IEEE 7th International Conference on Electronics Information and Emergency Communication, ICEIEC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "572--575",
editor = "Li Wenzheng and Seng-Pan U and Zhu Hongdan and Ni Shaowen",
booktitle = "Proceedings of 2017 IEEE 7th International Conference on Electronics Information and Emergency Communication, ICEIEC 2017",
}