{"title":"The Cost-Effective Video Stabilization Method for Wearable Camera","authors":"Chao-Ho Chen, Chia-En Lin, Tsong-Yi Chen, Da-Jinn Wang, Cheng-Fu Liao, Cheng-Kang Wen","doi":"10.1109/ICCE-Taiwan55306.2022.9869216","DOIUrl":null,"url":null,"abstract":"This paper presents a cost-effective video stabilization method for fast and large-shaking frames. To achieve real-time and high-quality video stabilization for fast and large-shaking frames, the main strategy of the proposed method is to find the optimal feature-point match to generate the better transformation matrix. Besides, the image pre-processing is exploited to down-sample the picture and then set the ROI area for substantially increasing the speed of the subsequent processing without affecting the detection of feature points. The proposed method is more cost-effective in stabilization than other approaches, especially for fast and large-shaking frames (e.g., video-shooting while running) and can be applied to the wearable cameras, sports cameras, and vehicle cameras.","PeriodicalId":164671,"journal":{"name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Consumer Electronics - Taiwan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a cost-effective video stabilization method for fast and large-shaking frames. To achieve real-time and high-quality video stabilization for fast and large-shaking frames, the main strategy of the proposed method is to find the optimal feature-point match to generate the better transformation matrix. Besides, the image pre-processing is exploited to down-sample the picture and then set the ROI area for substantially increasing the speed of the subsequent processing without affecting the detection of feature points. The proposed method is more cost-effective in stabilization than other approaches, especially for fast and large-shaking frames (e.g., video-shooting while running) and can be applied to the wearable cameras, sports cameras, and vehicle cameras.