YOLO 기반 외곽 사각형을 이용한 근접 돼지 분리Separation of Touching Pigs using YOLO-based Bounding Box
- Other Titles
- Separation of Touching Pigs using YOLO-based Bounding Box
- Authors
- 서지현; 주미소; 최윤창; 이준희; 정용화; 박대희
- Issue Date
- 2018
- Publisher
- 한국멀티미디어학회
- Keywords
- Pig Monitoring; Touching Pigs; Segmentation; Convolution Neural Network; YOLO
- Citation
- 멀티미디어학회논문지, v.21, no.2, pp.77 - 86
- Indexed
- KCI
- Journal Title
- 멀티미디어학회논문지
- Volume
- 21
- Number
- 2
- Start Page
- 77
- End Page
- 86
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/79837
- DOI
- 10.9717/kmms.2018.21.2.077
- ISSN
- 1229-7771
- Abstract
- Although separation of touching pigs in real-time is an important issue for a 24-h pig monitoring system, it is challenging to separate accurately the touching pigs in a crowded pig room. In this study, we propose a separation method for touching pigs using the information generated from Convolutional Neural Network(CNN). Especially, we apply one of the CNN-based object detection methods(i.e., You Look Only Once, YOLO) to solve the touching objects separation problem in an active manner. First, we evaluate and select the bounding boxes generated from YOLO, and then separate touching pigs by analyzing the relations between the selected bounding boxes. Our experimental results show that the proposed method is more effective than widely-used methods for separating touching pigs, in terms of both accuracy and execution time.
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Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
- College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
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