Po-Chyi Su, Ching-Yu Wu, Long-Wang Huang, Chia-Yang Chiou
{"title":"Constant frame quality control for H.264/AVC","authors":"Po-Chyi Su, Ching-Yu Wu, Long-Wang Huang, Chia-Yang Chiou","doi":"10.1017/ATSIP.2013.4","DOIUrl":"https://doi.org/10.1017/ATSIP.2013.4","url":null,"abstract":"A frame quality control mechanism for H.264/AVC is proposed in this research. The research objective is to ensure that a suitable Quantization Parameter (QP) can be assigned to each frame so that the target frame quality can be achieved. One application is consistently maintaining the frame quality during the encoding process to facilitate such applications of video archiving or surveillance. A single-parameter Distortion to Quantization (D-Q) model is derived by training a large number of frame blocks and this model parameter can be determined by the frame content. Given the target quality for a video frame, we can then select an appropriate QP according to the proposed D-Q model. The model refinement and QP adjustment of subsequent frames can be applied according to the coding results of previous data. Structural Similarity (SSIM) is chosen as the quality measurement to demonstrate the feasibility of the proposed framework.","PeriodicalId":248110,"journal":{"name":"Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114825141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shota Kawabuchi, C. Miyajima, N. Kitaoka, K. Takeda
{"title":"Subjective similarity of music: Data collection for individuality analysis","authors":"Shota Kawabuchi, C. Miyajima, N. Kitaoka, K. Takeda","doi":"10.1121/1.4709083","DOIUrl":"https://doi.org/10.1121/1.4709083","url":null,"abstract":"We describe a method of estimating subjective music similarity from acoustic music similarity. Recently, there have been many studies on the topic of music information retrieval, but there continues to be difficulty improving retrieval precision. For this reason, in this study we analyze the individuality of subjective music similarity. We collected subjective music similarity evaluation data for individuality analysis using songs in the RWC music database, a widely used database in the field of music information processing. A total of 27 subjects listened to pairs of music tracks, and evaluated each pair as similar or dissimilar. They also selected the components of the music (melody, tempo/rhythm, vocals, instruments) that were similar. Each subject evaluated the same 200 pairs of songs, thus the individuality of the evaluation can be easily analyzed. Using the collected data, we trained individualized distance functions between songs, in order to estimate subjective similarity and analyze individuality.","PeriodicalId":248110,"journal":{"name":"Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128148985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}