Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662023
Wen Yang, O. Au, Jingjing Dai, Feng Zou, Chao Pang, Yu Liu
Motion estimation as well as the corresponding motion compensation is a core part of modern video coding standards, which highly improves the compression efficiency. On the other hand, motion information takes considerable portion of compressed bit stream, especially in low bit rate situation. In this paper, an efficient motion vector prediction algorithm is proposed to minimize the bits used for coding the motion information. First, a possible motion vector predictor (MVP) candidate set (CS) including several scaled spatial and temporal predictors is defined. To increase the diversity of predictors, the spatial predictor is adaptively changed based on current distribution of neighboring motion vectors. After that, adaptive template matching technique is applied to remove non-effective predictors from the CS so that the bits used for the MVP index can be significantly reduced. As the final MVP is chosen based on minimum motion vector difference criterion, a guessing strategy is further introduced so that in some situations the bits consumed by signaling the MVP index to the decoder can be totally omitted. The experimental results indicate that the proposed method can achieve an average bit rate reduction of 5.9% compared with the H.264 standard.
{"title":"Motion vector coding algorithm based on adaptive template matching","authors":"Wen Yang, O. Au, Jingjing Dai, Feng Zou, Chao Pang, Yu Liu","doi":"10.1109/MMSP.2010.5662023","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662023","url":null,"abstract":"Motion estimation as well as the corresponding motion compensation is a core part of modern video coding standards, which highly improves the compression efficiency. On the other hand, motion information takes considerable portion of compressed bit stream, especially in low bit rate situation. In this paper, an efficient motion vector prediction algorithm is proposed to minimize the bits used for coding the motion information. First, a possible motion vector predictor (MVP) candidate set (CS) including several scaled spatial and temporal predictors is defined. To increase the diversity of predictors, the spatial predictor is adaptively changed based on current distribution of neighboring motion vectors. After that, adaptive template matching technique is applied to remove non-effective predictors from the CS so that the bits used for the MVP index can be significantly reduced. As the final MVP is chosen based on minimum motion vector difference criterion, a guessing strategy is further introduced so that in some situations the bits consumed by signaling the MVP index to the decoder can be totally omitted. The experimental results indicate that the proposed method can achieve an average bit rate reduction of 5.9% compared with the H.264 standard.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117337709","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662028
Seungju Han, Jae-Joon Han, Youngkyoo Hwang, Jungbae Kim, Won-Chul Bang, J. D. Kim, Chang-Yeong Kim
The recent online networked virtual worlds such as SecondLife, World of Warcraft and Lineage have been increasingly popular. A life-scale virtual world presentation and the intuitive interaction between the users and the virtual worlds would provide more natural and immersive experience for users. The emergence of novel interaction technologies such as sensing the facial expression and the motion of the users and the real world environments could be used to provide a strong connection between them. For the wide acceptance and use of the virtual world, a various type of novel interaction devices should have a unified interaction formats between the real world and the virtual world and interoperability among virtual worlds. Thus, MPEG-V Media Context and Control (ISO/IEC 23005) standardizes such connecting information. The paper provides an overview and its usage example of MPEG-V from the real world to the virtual world (R2V) on interfaces for controlling avatars and virtual objects in the virtual world by the real world devices. In particular, we investigate how the MPEG-V framework can be applied for the facial animation of an avatar in various types of virtual worlds.
{"title":"Controlling virtual world by the real world devices with an MPEG-V framework","authors":"Seungju Han, Jae-Joon Han, Youngkyoo Hwang, Jungbae Kim, Won-Chul Bang, J. D. Kim, Chang-Yeong Kim","doi":"10.1109/MMSP.2010.5662028","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662028","url":null,"abstract":"The recent online networked virtual worlds such as SecondLife, World of Warcraft and Lineage have been increasingly popular. A life-scale virtual world presentation and the intuitive interaction between the users and the virtual worlds would provide more natural and immersive experience for users. The emergence of novel interaction technologies such as sensing the facial expression and the motion of the users and the real world environments could be used to provide a strong connection between them. For the wide acceptance and use of the virtual world, a various type of novel interaction devices should have a unified interaction formats between the real world and the virtual world and interoperability among virtual worlds. Thus, MPEG-V Media Context and Control (ISO/IEC 23005) standardizes such connecting information. The paper provides an overview and its usage example of MPEG-V from the real world to the virtual world (R2V) on interfaces for controlling avatars and virtual objects in the virtual world by the real world devices. In particular, we investigate how the MPEG-V framework can be applied for the facial animation of an avatar in various types of virtual worlds.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127372020","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662066
V. Estellers, J. Thiran
In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of asynchrony. We show that audio-visual models should consider asynchrony within word boundaries and not at phoneme level. The second approach to the problem includes an additional processing of the features before being used for recognition. The proposed technique aligns the temporal evolution of the audio and video streams in terms of a speech-recognition system and enables the use of simpler statistical models for classification. On both cases we report experiments with the CUAVE database, showing the improvements obtained with the proposed asynchronous model and feature processing technique compared to traditional systems.
{"title":"Overcoming asynchrony in Audio-Visual Speech Recognition","authors":"V. Estellers, J. Thiran","doi":"10.1109/MMSP.2010.5662066","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662066","url":null,"abstract":"In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of asynchrony. We show that audio-visual models should consider asynchrony within word boundaries and not at phoneme level. The second approach to the problem includes an additional processing of the features before being used for recognition. The proposed technique aligns the temporal evolution of the audio and video streams in terms of a speech-recognition system and enables the use of simpler statistical models for classification. On both cases we report experiments with the CUAVE database, showing the improvements obtained with the proposed asynchronous model and feature processing technique compared to traditional systems.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130315000","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662001
A. A. Moghadam, H. Radha
We consider the problem of recovering a signal/image (x) with a k-sparse representation, from hybrid (complex and real), noiseless linear samples (y) using a mixture of complex-valued sparse and real-valued dense projections within a single matrix. The proposed Hybrid Compressed Sensing (HCS) employs the complex-sparse part of the projection matrix to divide the n-dimensional signal (x) into subsets. In turn, each subset of the signal (coefficients) is mapped onto a complex sample of the measurement vector (y). Under a worst-case scenario of such sparsity-induced mapping, when the number of complex sparse measurements is sufficiently large then this mapping leads to the isolation of a significant fraction of the k non-zero coefficients into different complex measurement samples from y. Using a simple property of complex numbers (namely complex phases) one can identify the isolated non-zeros of x. After reducing the effect of the identified non-zero coefficients from the compressive samples, we utilize the real-valued dense submatrix to form a full rank system of equations to recover the signal values in the remaining indices (that are not recovered by the sparse complex projection part). We show that the proposed hybrid approach can recover a k-sparse signal (with high probability) while requiring only m ≈ 3√n/2k real measurements (where each complex sample is counted as two real measurements). We also derive expressions for the optimal mix of complex-sparse and real-dense rows within an HCS projection matrix. Further, in a practical range of sparsity ratio (k/n) suitable for images, the hybrid approach outperforms even the most complex compressed sensing frameworks (namely basis pursuit with dense Gaussian matrices). The theoretical complexity of HCS is less than the complexity of solving a full-rank system of m linear equations. In practice, the complexity can be lower than this bound.
{"title":"Hybrid Compressed Sensing of images","authors":"A. A. Moghadam, H. Radha","doi":"10.1109/MMSP.2010.5662001","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662001","url":null,"abstract":"We consider the problem of recovering a signal/image (x) with a k-sparse representation, from hybrid (complex and real), noiseless linear samples (y) using a mixture of complex-valued sparse and real-valued dense projections within a single matrix. The proposed Hybrid Compressed Sensing (HCS) employs the complex-sparse part of the projection matrix to divide the n-dimensional signal (x) into subsets. In turn, each subset of the signal (coefficients) is mapped onto a complex sample of the measurement vector (y). Under a worst-case scenario of such sparsity-induced mapping, when the number of complex sparse measurements is sufficiently large then this mapping leads to the isolation of a significant fraction of the k non-zero coefficients into different complex measurement samples from y. Using a simple property of complex numbers (namely complex phases) one can identify the isolated non-zeros of x. After reducing the effect of the identified non-zero coefficients from the compressive samples, we utilize the real-valued dense submatrix to form a full rank system of equations to recover the signal values in the remaining indices (that are not recovered by the sparse complex projection part). We show that the proposed hybrid approach can recover a k-sparse signal (with high probability) while requiring only m ≈ 3√n/2k real measurements (where each complex sample is counted as two real measurements). We also derive expressions for the optimal mix of complex-sparse and real-dense rows within an HCS projection matrix. Further, in a practical range of sparsity ratio (k/n) suitable for images, the hybrid approach outperforms even the most complex compressed sensing frameworks (namely basis pursuit with dense Gaussian matrices). The theoretical complexity of HCS is less than the complexity of solving a full-rank system of m linear equations. In practice, the complexity can be lower than this bound.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131158365","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662022
Jean-Marc Thiesse, Joël Jung, M. Antonini
2010 appears to be the launching date for new compression activities intended to challenge the current video compression standard H.264/AVC. Several improvements of this standard are already known like competition-based motion vector prediction. However the targeted 50% bitrate saving for equivalent quality is not yet achieved. In this context, this paper proposes to reduce the signaling information resulting from this vector competition, by using data hiding techniques. As data hiding and video compression traditionally have contradictory goals, a study of data hiding is first performed. Then, an efficient way of using data hiding for video compression is proposed. The main idea is to hide the indices into appropriately selected chroma and luma transform coefficients. To minimize the prediction errors, the modification is performed via a rate-distortion optimization. Objective improvements (up to 2.3% bitrate saving) and subjective assess ment of chroma loss are reported and analyzed for several sequences.
{"title":"Data hiding of motion information in chroma and luma samples for video compression","authors":"Jean-Marc Thiesse, Joël Jung, M. Antonini","doi":"10.1109/MMSP.2010.5662022","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662022","url":null,"abstract":"2010 appears to be the launching date for new compression activities intended to challenge the current video compression standard H.264/AVC. Several improvements of this standard are already known like competition-based motion vector prediction. However the targeted 50% bitrate saving for equivalent quality is not yet achieved. In this context, this paper proposes to reduce the signaling information resulting from this vector competition, by using data hiding techniques. As data hiding and video compression traditionally have contradictory goals, a study of data hiding is first performed. Then, an efficient way of using data hiding for video compression is proposed. The main idea is to hide the indices into appropriately selected chroma and luma transform coefficients. To minimize the prediction errors, the modification is performed via a rate-distortion optimization. Objective improvements (up to 2.3% bitrate saving) and subjective assess ment of chroma loss are reported and analyzed for several sequences.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131246292","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662046
H. Benhabiles, G. Lavoué, Jean-Philippe Vandeborre, M. Daoudi
In this paper we present a subjective quality assessment experiment for 3D-mesh segmentation. For this end, we carefully designed a protocol with respect to several factors namely the rendering conditions, the possible interactions, the rating range, and the number of human subjects. To carry out the subjective experiment, more than 40 human observers have rated a set of 250 segmentation results issued from various algorithms. The obtained Mean Opinion Scores, which represent the human subjects' point of view toward the quality of each segmentation, have then been used to evaluate both the quality of automatic segmentation algorithms and the quality of similarity metrics used in recent mesh segmentation benchmarking systems.
{"title":"A subjective experiment for 3D-mesh segmentation evaluation","authors":"H. Benhabiles, G. Lavoué, Jean-Philippe Vandeborre, M. Daoudi","doi":"10.1109/MMSP.2010.5662046","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662046","url":null,"abstract":"In this paper we present a subjective quality assessment experiment for 3D-mesh segmentation. For this end, we carefully designed a protocol with respect to several factors namely the rendering conditions, the possible interactions, the rating range, and the number of human subjects. To carry out the subjective experiment, more than 40 human observers have rated a set of 250 segmentation results issued from various algorithms. The obtained Mean Opinion Scores, which represent the human subjects' point of view toward the quality of each segmentation, have then been used to evaluate both the quality of automatic segmentation algorithms and the quality of similarity metrics used in recent mesh segmentation benchmarking systems.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"684 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132868006","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662071
A. Bakhtiari, N. Bouguila
In many applications it is necessary to be able to classify images in a database accurately and with acceptable speed. The main problem is to assign different images to right categories. The later problem becomes more challenging while dealing with large databases with many categories and subcategories. In this paper we propose a novel classification method based on an adopted hierarchical Dirichlet generative model, previously proposed for corpora document classification. In order to adopt the model to work with image data we use the bag of visual words model. We show that if properly applied the model can achieve adequate results for hierarchical image classification. Experimental results are presented and discussed to show the merits of the proposed approach.
{"title":"A hierarchical statistical model for object classification","authors":"A. Bakhtiari, N. Bouguila","doi":"10.1109/MMSP.2010.5662071","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662071","url":null,"abstract":"In many applications it is necessary to be able to classify images in a database accurately and with acceptable speed. The main problem is to assign different images to right categories. The later problem becomes more challenging while dealing with large databases with many categories and subcategories. In this paper we propose a novel classification method based on an adopted hierarchical Dirichlet generative model, previously proposed for corpora document classification. In order to adopt the model to work with image data we use the bag of visual words model. We show that if properly applied the model can achieve adequate results for hierarchical image classification. Experimental results are presented and discussed to show the merits of the proposed approach.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"503 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134031344","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662011
Wan-Chien Chiou, Yi-Lei Chen, Chiou-Ting Hsu
This paper proposes an automatic color transfer method for processing images with complex content based on intrinsic component. Although several automatic color transfer methods has been proposed by including region information and/or using multiple references, these methods tend to become ineffective when processing images with complex content and lighting variation. In this paper, our goal is to incorporate the idea of intrinsic component to better characterize the local organization within an image and to reduce the color-bleeding artifact across complex regions. Using intrinsic information, we first represent each image in region level and determine the best-matched reference region for each target region. Next, we conduct color transfer between the best-matched region pairs and perform weighted color transfer for pixels across complex regions in a de-correlated color space. Both subjective and objective evaluation of our experiments demonstrates that the proposed method outperforms the existing methods.
{"title":"Color transfer for complex content images based on intrinsic component","authors":"Wan-Chien Chiou, Yi-Lei Chen, Chiou-Ting Hsu","doi":"10.1109/MMSP.2010.5662011","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662011","url":null,"abstract":"This paper proposes an automatic color transfer method for processing images with complex content based on intrinsic component. Although several automatic color transfer methods has been proposed by including region information and/or using multiple references, these methods tend to become ineffective when processing images with complex content and lighting variation. In this paper, our goal is to incorporate the idea of intrinsic component to better characterize the local organization within an image and to reduce the color-bleeding artifact across complex regions. Using intrinsic information, we first represent each image in region level and determine the best-matched reference region for each target region. Next, we conduct color transfer between the best-matched region pairs and perform weighted color transfer for pixels across complex regions in a de-correlated color space. Both subjective and objective evaluation of our experiments demonstrates that the proposed method outperforms the existing methods.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124033100","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662008
David Antonio Gómez Jáuregui, P. Horain, Manoj Kumar Rajagopal, S. S. Karri
Particle filtering is known as a robust approach for motion tracking by vision, at the cost of heavy computation in a high dimensional pose space. In this work, we describe a number of heuristics that we demonstrate to jointly improve robustness and real-time for motion capture. 3D human motion capture by monocular vision without markers can be achieved in realtime by registering a 3D articulated model on a video. First, we search the high-dimensional space of 3D poses by generating new hypotheses (or particles) with equivalent 2D projection by kinematic flipping. Second, we use a semi-deterministic particle prediction based on local optimization. Third, we deterministi-cally resample the probability distribution for a more efficient selection of particles. Particles (or poses) are evaluated using a match cost function and penalized with a Gaussian probability pose distribution learned off-line. In order to achieve real-time, measurement step is parallelized on GPU using the OpenCL API. We present experimental results demonstrating robust real-time 3D motion capture with a consumer computer and webcam.
{"title":"Real-time particle filtering with heuristics for 3D motion capture by monocular vision","authors":"David Antonio Gómez Jáuregui, P. Horain, Manoj Kumar Rajagopal, S. S. Karri","doi":"10.1109/MMSP.2010.5662008","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662008","url":null,"abstract":"Particle filtering is known as a robust approach for motion tracking by vision, at the cost of heavy computation in a high dimensional pose space. In this work, we describe a number of heuristics that we demonstrate to jointly improve robustness and real-time for motion capture. 3D human motion capture by monocular vision without markers can be achieved in realtime by registering a 3D articulated model on a video. First, we search the high-dimensional space of 3D poses by generating new hypotheses (or particles) with equivalent 2D projection by kinematic flipping. Second, we use a semi-deterministic particle prediction based on local optimization. Third, we deterministi-cally resample the probability distribution for a more efficient selection of particles. Particles (or poses) are evaluated using a match cost function and penalized with a Gaussian probability pose distribution learned off-line. In order to achieve real-time, measurement step is parallelized on GPU using the OpenCL API. We present experimental results demonstrating robust real-time 3D motion capture with a consumer computer and webcam.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124080466","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}
Pub Date : 2010-12-10DOI: 10.1109/MMSP.2010.5662055
Ester Gutiérrez, Hyunggon Park, P. Frossard
In this paper, we present a solution to efficient multimedia streaming applications over P2P networks based on the foresighted resource reciprocation strategy. We study several priority functions that can explicitly consider the timing constraints and the importance of each data segment in terms of multimedia quality, and successfully incorporate them into the foresighted resource reciprocation strategy. This enables peers to enhance their multimedia streaming capability. The simulation results confirm that the proposed approach outperforms existing algorithms such as tit-for-tat in BitTorrent and BiToS solutions.
{"title":"An improved foresighted resource reciprocation strategy for multimedia streaming applications","authors":"Ester Gutiérrez, Hyunggon Park, P. Frossard","doi":"10.1109/MMSP.2010.5662055","DOIUrl":"https://doi.org/10.1109/MMSP.2010.5662055","url":null,"abstract":"In this paper, we present a solution to efficient multimedia streaming applications over P2P networks based on the foresighted resource reciprocation strategy. We study several priority functions that can explicitly consider the timing constraints and the importance of each data segment in terms of multimedia quality, and successfully incorporate them into the foresighted resource reciprocation strategy. This enables peers to enhance their multimedia streaming capability. The simulation results confirm that the proposed approach outperforms existing algorithms such as tit-for-tat in BitTorrent and BiToS solutions.","PeriodicalId":105774,"journal":{"name":"2010 IEEE International Workshop on Multimedia Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114402849","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}
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