Vast Amounts of Video Data Clean Algorithm Base on Bradley-Terry Model
Binwen Cao, Li Chen, Hui Lie
Available Online February 2017.
- https://doi.org/10.2991/emcm-16.2017.21How to use a DOI?
- Bradley-terry model; ELO rating system; Video quality assessment; Data cleaning
- Traditional video data cleaning method is to use video quality subjective labeling to achieve. This method relies on the subjective and objective factors such as the level of expert knowledge of the observer and the observing environment, so that a high accuracy rate cannot be ensured, and in the massive data conditions need to consume a lot of manpower and time. In this paper, Bradley-Terry model is applied to the field of video cleaning for the first time, let each observer will randomly selected two videos from the sample than Choose the better of the two according to their quality, then we use the ELO Rating System points the results, finally an ordered set is obtained. We use the real-time monitoring of video data to complete the experiment and evaluate our algorithm with stability and effectiveness. The results show that the proposed video quality sorting method has good stability and accuracy, and can be finely and quickly sort the data by their quality in the video big data environment. Experimental results show that the algorithm can clean the video data accurately and quickly under the condition of massive video.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Binwen Cao AU - Li Chen AU - Hui Lie PY - 2017/02 DA - 2017/02 TI - Vast Amounts of Video Data Clean Algorithm Base on Bradley-Terry Model BT - 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016) PB - Atlantis Press SP - 104 EP - 110 SN - 2352-538X UR - https://doi.org/10.2991/emcm-16.2017.21 DO - https://doi.org/10.2991/emcm-16.2017.21 ID - Cao2017/02 ER -