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JBE, vol. 27, no. 4, pp.499-510, July, 2022


Video Content Editing System for Senior Video Creator based on Video Analysis Techniques

Dalwon Jang, Jaewon Lee, and JongSeol Lee

C.A E-mail:


This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

Keyword: Video editing, Video creator, Video shot detection, Video analysis

[1] J. Lee, “A Study on Types of Short-form Video Contents,” Humanities Contents, Vol. 58, pp.121-139, 2020. doi:
[2] J.-H. Kwon, “A Study on the Planning of a Space for Senior Citizens Using Digital Contents,” Journal of Digital Convergence, Vol. 18, No. 5, pp. 257-267, 2020. doi:
[3] J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You only look once: Unified, real-time object detection,” Proceedings of the IEEE International conference on computer vision and pattern recognition(CVPR), Las Vegas, NV, USA, pp. 779–788, 2016. doi:
[4] P. Viola and M. J. Jones, “Robust real-time face detection,” International Journal of Computer Vision. Vol. 57, pp. 137–154, 2004 doi:
[5] X. Yi and M. Eramian, “LBP-based segmentation of defocus blur,” IEEE Trans. Image Process, Vol. 25, no. 4, pp. 1626–1638, Apr. 2016. doi:
[6] W. Zhao, F. Zhao, D. Wang, and H. Lu., “Defocus blur detection via multi-stream bottom-top-bottom fully convolutional network,” Proceeding of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), Salt Lake City, UT, USA, pp 3080–3088, 2018. doi:
[7] C. Tang, X. Zhu, X. Liu, L. Wang, and A. Zomaya, “DeFusionNET: Defocus blur detection via recurrently fusing and refining multi-scale deep features,” Proceeding of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), Long Beach, CA, USA, pp. 2700–2709, 2019. doi:
[8] J. Shi, L. Xu, and J. Jia, “Discriminative blur detection features,” Proceeding of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), Columbus, OH, USA, pp. 2965–2972, 2014. doi:
[9] Y. Gao, Y. Lai and Y.Liu, “Fast Video Shot Boundary Detection Based on Visual Perception”, Proceeding of IEEE International Conference on Consumer Electronics(ICCE), Las Vegas, NV, USA, pp.1-4, 2019. doi:
[10] M. Gygli, “Ridiculously fast shot boundary detection with fully convolutional neural networks,” Proceeding of International Conference on Content-Based Multimedia Indexing(CBMI), La Rochelle, France, Sep. 2018, pp. 1–4. doi:
[11] M. Brindha and R. Amsaveni, “Shot change detection on news videos using color histogram and edge based approaches,” Proceeding of IEEE International Conference on Advances in Computer Applications(ICACA), Coimbatore, India, pp.50-54, 2016. doi:
[12] G. Kwon and J. Kwon, “A Study on the Usability of Video Authoring Tool Application for Active Senior,” Journal of Next-generation Convergence Information Services Technology, 9, no.4 (2020) : 351-361. doi:
[13] S.-D. Park, “Education of media by production of image contents - Focusing on Non-Linear Editing,” Journal of the Korea Institute of Information and Communication Engineering, Vol. 23, No. 9, 1096~1103. doi:


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