{"title":"Low-Complexity Adaptive Streaming via Optimized A Priori Media Pruning","authors":"Jacob Chakareski, P. Frossard","doi":"10.1109/MMSP.2005.248610","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248610","url":null,"abstract":"Source pruning is performed whenever the data rate of the compressed source exceeds the available communication or storage resources. In this paper, we propose a framework for rate-distortion optimized pruning of a video source. The framework selects which packets, if any, from the compressed representation of the source should be discarded so that the data rate of the pruned source is adjusted accordingly, while the resulting reconstruction distortion is minimized. The framework relies on a rate-distortion preamble that is created at compression time for the video source and that comprises the video packets' sizes, interdependencies and distortion importance. As one application of the pruning framework, we design a low-complexity rate-distortion optimized ARQ scheme for video streaming. In the experiments, we examine the performance of the pruning framework depending on the employed distortion model that describes the effect of packet interdependencies on the reconstruction quality. In addition, our experimental results show that the enhanced ARQ technique provides a significant performance gain over a conventional system for video streaming that does not take into account the different importance of the individual video packets. These gains are achieved without an increase in packet scheduling complexity, which makes the proposed technique suitable for online R-D optimized streaming","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122701390","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}
{"title":"An Autonomous Dance Scoring System Using Marker-based Motion Capture","authors":"Huayue Chen, G. Qian, J. James","doi":"10.1109/MMSP.2005.248666","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248666","url":null,"abstract":"In this paper, we present a dance scoring system developed using marker-based motion capture. The dance score is outputted in form of Labanotation. Promising results have been obtained using the proposed dance scoring system","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127274496","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}
{"title":"Enhanced Video Stream Switching Schemes for H.264","authors":"Xiaosong Zhou, C.-C. Jay Kuo","doi":"10.1109/MMSP.2005.248597","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248597","url":null,"abstract":"Two enhanced video stream switching schemes for H.264 are proposed aiming at prompt switching among compressed video streams coded at different quality levels and bit rates. The stream switching scheme using primary and secondary SP/SI pictures in H.264 is effective in switching, but degrades the compression efficiency of the transmitted stream even if the switching operation does not take place. In the two proposed schemes, no modification is made to the original compressed streams (namely, no primary SP picture is adopted) so that compression efficiency is maintained at switching points. As a result, switching points can be assigned flexibly in our enhanced schemes according to the need of applications and network conditions without worrying about the bit rate overhead. When switching occurs, the proposed schemes use a new picture type-DIFF (difference picture) in different ways to compensate the mismatch of reference frames. The first proposed scheme is designed to simplify the implementation while the second scheme is designed to further reduce the bit rate overhead. It is shown by experimental results that both of the proposed schemes outperform the switching scheme defined in H.264 and they are able to realize prompt stream switching without noticeable quality degradation and have a small bit rate overhead only when the actual switching operation occurs","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122321024","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}
{"title":"Attentive Behavior Detection by Non-Linear Head Pose Embedding and Mapping","authors":"Nan Hu, Weimin Huang","doi":"10.1109/MMSP.2005.248585","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248585","url":null,"abstract":"In this paper, we present a new scheme to robustly detect a human attentive behavior, i.e., a frequent change in focus of attention (FCFA) from video sequences. The FCFA behavior can be easily perceived by people as temporal changes of human head pose. Here, we propose a non-linear head pose embedding and mapping algorithm to detect the pose in each frame of the sequence. Developed from ISOMAP, we learn a person-independent and non-linear embedding space (we call it a 2-D feature space) for different head poses. A non-linear interpolation mapping followed by an adaptive local fitting method is designed to map new frames into the 2-D feature space where head poses can be further obtained. An entropy classifier is then proposed on each sequence to detect the FCFA behavior. Experiments reported in this paper showed robust results","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125857768","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}
{"title":"Characterization of Error Diffusion Halftone Images based on Subband Decompostion","authors":"Hua Fang, Xiqun Lu","doi":"10.1109/MMSP.2005.248576","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248576","url":null,"abstract":"Digital halftoning creates the illusion of continuous tone output for a binary device. Halftoning using error diffusion reduces local quantization error by filtering the quantization error in a feedback loop. In this paper, we present a new scheme to evaluate error diffusion halftoning. An integer-coefficient filter bank is applied to an error diffusion halftone image to obtain frequency subbands. Based on these subband images, statistical distribution measurements and the correlations between the original image and the residual image are defined to evaluate the qualities of several error diffusion algorithms. Experimental results show that the rank of several error diffusion algorithms based on our gauges is consistent with the results of previous research works","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126609055","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}
{"title":"Music Identification Using Embedded HMM","authors":"Kai Chen, Sheng Gao, Peiqi Chai, Qibin Sun","doi":"10.1109/MMSP.2005.248550","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248550","url":null,"abstract":"In this paper, we propose a new method for music identification based on embedded hidden Markov model (EHMM). Differing from conventional HMM, the EHMM estimates the emission probability of its external HMM from the second, state specific HMM, which is referred as internal HMM. EHMM clusters the feature blocks with its external HMM and describes spectral and the temporal structures of each feature block with its internal HMM. Our analysis and experimental results show that the proposed method for music identification achieves higher accuracy and lower complexity than previous approaches","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127873847","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}
{"title":"Rate Control Based on Zero-Residue Pre-Selection for Video Transcoding","authors":"C. Ho, O. Au, S. Chan, H. Wong, S. Yip","doi":"10.1109/MMSP.2005.248628","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248628","url":null,"abstract":"A common issue in video transcoding for heterogeneous network environment is to efficiently and accurately reduce the bit-rate such that the distortion is minimized under a given rate constraint. To convert the bit-rate of an encoded video to match the channel capacity, in general, re-quantization is done on the DCT coefficients with larger quantization step size. Most existing rate control algorithms for video transcoding in the literature calculate quantization parameters (QPs) of macroblocks (MBs) based on a relationship between certain properties of coded video and bit-rate. They reduce the computational complexity by simplifying the R-D model and reusing the statistics information of input video. In this paper, we propose a zero-residue pre-selection (ZRPS) mechanism to select only a portion of MBs to apply the rate control in video transcoding. TMN-8 is used to evaluate the impact of ZRPS. Experimental results show that, as compared to the original TMN-8 rate control scheme, TMN-8 with ZRPS achieves up to 1.60 dB gain, in term of PSNR, and requires less than 50% of the computational complexity compared to TMN-8, depending on the characteristics of the video content","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116987465","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}
{"title":"Detecting Interlaced or Progressive Source of Video","authors":"S. Keller, K. S. Pedersen, F. Lauze","doi":"10.1109/MMSP.2005.248555","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248555","url":null,"abstract":"In this paper we introduce an algorithm - commonly known as a film mode detector - for separating progressive source video from interlaced source video. Due to interlacing artifacts in the presence of motion, a difference in isophote curvature can be measured and a threshold for effective classification can be set. This can be used in a video converter to ensure high quality output. We studied and compared the two approaches","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132830424","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}
{"title":"Spectral Images and Features Co-Clustering with Application to Content-based Image Retrieval","authors":"Jian Guan, G. Qiu, X. Xue","doi":"10.1109/MMSP.2005.248647","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248647","url":null,"abstract":"In this paper, we present a spectral graph partitioning method for the co-clustering of images and features. We present experimental results, which show that spectral co-clustering has computational advantages over traditional k-means algorithm, especially when the dimensionalities of feature vectors are high. In the context of image clustering, we also show that spectral co-clustering gives better performances. We advocate that the images and features co-clustering framework offers new opportunities for developing advanced image database management technology and illustrate a possible scheme for exploiting the co-clustering results for developing a novel content-based image retrieval method","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134243030","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}
Axel Weissenfeld, Kang Liu, S. Klomp, J. Ostermann
{"title":"Personalized Unit Selection for an Image-based Facial Animation System","authors":"Axel Weissenfeld, Kang Liu, S. Klomp, J. Ostermann","doi":"10.1109/MMSP.2005.248608","DOIUrl":"https://doi.org/10.1109/MMSP.2005.248608","url":null,"abstract":"This paper describes an image-based facial animation system, which consists of the audiovisual analysis of a human subject and the synthesis of a photo-realistic facial animation. The unit selection algorithm selects for a given audio output the best mouth samples from the database by assigning two costs, the phonetic context and the visual distance between two consecutive samples. Here a novel approach to adapt the unit selection algorithm to an individual human subject is presented, such that a photo-realistic facial animation can be generated","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128518954","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}