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http://dx.doi.org/10.6109/jkiice.2021.25.12.1790

Building Method an Image Dataset for Tracking Objects in a Video  

Kim, Ji-Seong (Department of Computer Engineering, Dong-Eui University)
Heo, Gyeongyong (Department of Electronic Engineering, Dong-eui University)
Jang, Si-Woong (Department of Computer Engineering, Dong-Eui University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.12, 2021 , pp. 1790-1796 More about this Journal
Abstract
A large amount of image data sets are required for image deep learning, and there are many differences in the method of obtaining images and constructing image data sets depending on the type of object. In this paper, we presented a method of constructing an image data set for deep learning and analyzed the performance that varies depending on the object to be tracked. We took a video by rotating the object, and then created a data set by segmenting the video using the proposed data set construction method. As a result of performance analysis, detection rate was more than 95%, and detection rate of objects with little change in shape was higher performance. It is considered that it is effective to use the data set construction method presented in this paper for a situation in which it is difficult to obtain image data and to track an object with little change in shape within a video.
Keywords
Artificial intelligence; Deep learning; Datasets; Object tracking;
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