{"title":"动画几何的时间可伸缩压缩","authors":"Sanjib Das, H. ShahJaimeen, P. Bora","doi":"10.1109/NCVPRIPG.2013.6776263","DOIUrl":null,"url":null,"abstract":"Animation geometry compression involves compressing the geometry data of dynamic three-dimensional (3D) triangular meshes representing the animation frames. The scalability issue of geometry compression addresses compressing the geometry in a single scale and decompressing it in multiple scales. One of the algorithms for animation geometry compression employs the skinning based motion prediction of vertices and the temporal wavelet transform (TWT) on the prediction errors. This paper presents an encoder and a decoder structure for achieving temporally scalable implementation of the algorithm. The frame-wise prediction errors due to motion based clustering of a group of affine transformed vertices are converted into a layered structure of the frames using the TWT. The affine transformation data of vertices, weights corresponding to each cluster of vertices and the wavelet coefficients of the prediction errors are quantized and encoded using the entropy coding. The resulting bit-stream is arranged in a layered structure to achieve temporal scalability. The base layer consists of the connectivity coded first frame, indices of the clusters of vertices, weights corresponding to each cluster of a vertex, the approximation sub-band of prediction error and the affine transformations corresponding to the approximation frames. The enhancement layers consist of the detailed sub-bands of prediction error and the affine transformations corresponding to the detailed frames. The scalable encoder and decoder are tested on some standard animation sequences and the experimental results show good performance in terms of scalable rates and distortions.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"321 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Temporally scalable compression of animation geometry\",\"authors\":\"Sanjib Das, H. ShahJaimeen, P. Bora\",\"doi\":\"10.1109/NCVPRIPG.2013.6776263\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Animation geometry compression involves compressing the geometry data of dynamic three-dimensional (3D) triangular meshes representing the animation frames. The scalability issue of geometry compression addresses compressing the geometry in a single scale and decompressing it in multiple scales. One of the algorithms for animation geometry compression employs the skinning based motion prediction of vertices and the temporal wavelet transform (TWT) on the prediction errors. This paper presents an encoder and a decoder structure for achieving temporally scalable implementation of the algorithm. The frame-wise prediction errors due to motion based clustering of a group of affine transformed vertices are converted into a layered structure of the frames using the TWT. The affine transformation data of vertices, weights corresponding to each cluster of vertices and the wavelet coefficients of the prediction errors are quantized and encoded using the entropy coding. The resulting bit-stream is arranged in a layered structure to achieve temporal scalability. The base layer consists of the connectivity coded first frame, indices of the clusters of vertices, weights corresponding to each cluster of a vertex, the approximation sub-band of prediction error and the affine transformations corresponding to the approximation frames. The enhancement layers consist of the detailed sub-bands of prediction error and the affine transformations corresponding to the detailed frames. The scalable encoder and decoder are tested on some standard animation sequences and the experimental results show good performance in terms of scalable rates and distortions.\",\"PeriodicalId\":436402,\"journal\":{\"name\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"volume\":\"321 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCVPRIPG.2013.6776263\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Temporally scalable compression of animation geometry
Animation geometry compression involves compressing the geometry data of dynamic three-dimensional (3D) triangular meshes representing the animation frames. The scalability issue of geometry compression addresses compressing the geometry in a single scale and decompressing it in multiple scales. One of the algorithms for animation geometry compression employs the skinning based motion prediction of vertices and the temporal wavelet transform (TWT) on the prediction errors. This paper presents an encoder and a decoder structure for achieving temporally scalable implementation of the algorithm. The frame-wise prediction errors due to motion based clustering of a group of affine transformed vertices are converted into a layered structure of the frames using the TWT. The affine transformation data of vertices, weights corresponding to each cluster of vertices and the wavelet coefficients of the prediction errors are quantized and encoded using the entropy coding. The resulting bit-stream is arranged in a layered structure to achieve temporal scalability. The base layer consists of the connectivity coded first frame, indices of the clusters of vertices, weights corresponding to each cluster of a vertex, the approximation sub-band of prediction error and the affine transformations corresponding to the approximation frames. The enhancement layers consist of the detailed sub-bands of prediction error and the affine transformations corresponding to the detailed frames. The scalable encoder and decoder are tested on some standard animation sequences and the experimental results show good performance in terms of scalable rates and distortions.