Pub Date : 2008-11-05DOI: 10.1109/MMSP.2008.4665113
K. Yoon, J. H. Kim
The macroblock (MB)-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. Although the conventional cost functions have showed a good performance in terms of rate and distortion, it still leaves room for improvement. To improve coding efficiency, we introduce a new cost function which considers two bit rates, motion vector and prediction error, and reconstruction error of MB. The filter which minimizes the proposed cost function is adaptively selected per MB. Experimental results show that the adaptive interpolation filter with the proposed cost function significantly improves the coding efficiency compared to ones using conventional cost function. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate reduction on average compared to H.264/AVC, respectively.
{"title":"Macroblock-based adaptive interpolation filter method using new filter selection in H.264/AVC","authors":"K. Yoon, J. H. Kim","doi":"10.1109/MMSP.2008.4665113","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665113","url":null,"abstract":"The macroblock (MB)-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. Although the conventional cost functions have showed a good performance in terms of rate and distortion, it still leaves room for improvement. To improve coding efficiency, we introduce a new cost function which considers two bit rates, motion vector and prediction error, and reconstruction error of MB. The filter which minimizes the proposed cost function is adaptively selected per MB. Experimental results show that the adaptive interpolation filter with the proposed cost function significantly improves the coding efficiency compared to ones using conventional cost function. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate reduction on average compared to H.264/AVC, respectively.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134345340","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665174
M. Kuribayashi, N. Akashi, M. Morii
Digital fingerprinting is used to trace back illegal users, where unique ID known as digital fingerprints is embedded into a content before distribution. On the generation of such fingerprints, one of the important properties is collusion-resistance. Binary codes for fingerprinting with a code length of theoretically minimum order were proposed by Tardos, and the related works mainly focused on the reduction of the code length were presented. In this paper, we present a concrete and systematic construction of the Tardospsilas fingerprinting code using a chaotic map. Using a statistical model for correlation scores, a proper threshold for detecting colluders is calculated. Furthermore, for the reduction of computational costs required for the detection, a hierarchical structure is introduced on the codewords. The collusion-resistance of the generated fingerprinting codes is evaluated by a computer simulation.
{"title":"On the systematic generation of Tardos’s fingerprinting codes","authors":"M. Kuribayashi, N. Akashi, M. Morii","doi":"10.1109/MMSP.2008.4665174","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665174","url":null,"abstract":"Digital fingerprinting is used to trace back illegal users, where unique ID known as digital fingerprints is embedded into a content before distribution. On the generation of such fingerprints, one of the important properties is collusion-resistance. Binary codes for fingerprinting with a code length of theoretically minimum order were proposed by Tardos, and the related works mainly focused on the reduction of the code length were presented. In this paper, we present a concrete and systematic construction of the Tardospsilas fingerprinting code using a chaotic map. Using a statistical model for correlation scores, a proper threshold for detecting colluders is calculated. Furthermore, for the reduction of computational costs required for the detection, a hierarchical structure is introduced on the codewords. The collusion-resistance of the generated fingerprinting codes is evaluated by a computer simulation.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125064244","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665141
M. Awrangjeb, Guojun Lu
The SIFT (scale invariant feature transform) has demonstrated its superior performance in identifying transformed images over many other approaches. However, both of its detection and matching stages are expensive, because a large number of keypoints are detected in the scale-space and each keypoint is described using a 128-dimensional vector. We present two possible solutions for feature-point reduction. First is to down scale the image before the SIFT keypoint detection and second is to use corners (instead of SIFT keypoints) which are visually significant, more robust, and much smaller in number than the SIFT keypoints. Either the curvature descriptor or the highly distinctive SIFT descriptors at corner locations can be used to represent corners.We then describe a new feature-point matching technique, which can be used for matching both the down-scaled SIFT keypoints and corners. Experimental results show that two feature-point reduction solutions combined with the SIFT descriptors and the proposed feature-point matching technique not only improve the computational efficiency and decrease the storage requirement, but also improve the transformed image identification accuracy (robustness).
{"title":"Efficient and effective transformed image identification","authors":"M. Awrangjeb, Guojun Lu","doi":"10.1109/MMSP.2008.4665141","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665141","url":null,"abstract":"The SIFT (scale invariant feature transform) has demonstrated its superior performance in identifying transformed images over many other approaches. However, both of its detection and matching stages are expensive, because a large number of keypoints are detected in the scale-space and each keypoint is described using a 128-dimensional vector. We present two possible solutions for feature-point reduction. First is to down scale the image before the SIFT keypoint detection and second is to use corners (instead of SIFT keypoints) which are visually significant, more robust, and much smaller in number than the SIFT keypoints. Either the curvature descriptor or the highly distinctive SIFT descriptors at corner locations can be used to represent corners.We then describe a new feature-point matching technique, which can be used for matching both the down-scaled SIFT keypoints and corners. Experimental results show that two feature-point reduction solutions combined with the SIFT descriptors and the proposed feature-point matching technique not only improve the computational efficiency and decrease the storage requirement, but also improve the transformed image identification accuracy (robustness).","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132234830","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665145
G. Herman, G. Ye, Jie Xu, Bang Zhang
In this paper we propose a new algorithm for region-based image categorization that is formulated as a multiple instance learning (MIL) problem. The proposed algorithm transforms the MIL problem into a traditional supervised learning problem, and solves it using a standard supervised learning method. The features used in the proposed algorithm are the hyperclique patterns which are ldquocondensedrdquo into a small set of discriminative features. Each hyperclique pattern consists of multiple strongly-correlated instances (i.e., features). As a result, hyperclique patterns are able to capture the information that are not shared by individual features. The advantages of the proposed algorithm over existing algorithms are threefold: (i) unlike some existing algorithms which use learning methods that are specifically designed for MIL or for certain datasets, the proposed algorithm uses a general-purpose standard supervised learning method, (ii) it uses a significantly small set of features which are empirically more discriminative than the PCA features (i.e. principal components), and (iii) it is simple and efficient and achieves a comparable performance to most state-of-the-art algorithms. The efficiency and good performance of the proposed algorithm make it a practical solution to general MIL problems. In this paper, we apply the proposed algorithm to both drug activity prediction and image categorization, and promising results are obtained.
{"title":"Region-based image categorization with reduced feature set","authors":"G. Herman, G. Ye, Jie Xu, Bang Zhang","doi":"10.1109/MMSP.2008.4665145","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665145","url":null,"abstract":"In this paper we propose a new algorithm for region-based image categorization that is formulated as a multiple instance learning (MIL) problem. The proposed algorithm transforms the MIL problem into a traditional supervised learning problem, and solves it using a standard supervised learning method. The features used in the proposed algorithm are the hyperclique patterns which are ldquocondensedrdquo into a small set of discriminative features. Each hyperclique pattern consists of multiple strongly-correlated instances (i.e., features). As a result, hyperclique patterns are able to capture the information that are not shared by individual features. The advantages of the proposed algorithm over existing algorithms are threefold: (i) unlike some existing algorithms which use learning methods that are specifically designed for MIL or for certain datasets, the proposed algorithm uses a general-purpose standard supervised learning method, (ii) it uses a significantly small set of features which are empirically more discriminative than the PCA features (i.e. principal components), and (iii) it is simple and efficient and achieves a comparable performance to most state-of-the-art algorithms. The efficiency and good performance of the proposed algorithm make it a practical solution to general MIL problems. In this paper, we apply the proposed algorithm to both drug activity prediction and image categorization, and promising results are obtained.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133243872","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665214
Kyu Jeong Han, P. Georgiou, Shrikanth S. Narayanan
In this paper, we propose a novel approach to speaker diarization of spontaneous meetings in our own multimodal SmartRoom environment. The proposed speaker diarization system first applies a sequential clustering concept to segmentation of a given audio data source, and then performs agglomerative hierarchical clustering for speaker-specific classification (or speaker clustering) of speech segments. The speaker clustering algorithm utilizes an incremental Gaussian mixture cluster modeling strategy, and a stopping point estimation method based on information change rate. Through experiments on various meeting conversation data of approximately 200 minutes total length, this system is demonstrated to provide diarization error rate of 18.90% on average.
{"title":"The SAIL speaker diarization system for analysis of spontaneous meetings","authors":"Kyu Jeong Han, P. Georgiou, Shrikanth S. Narayanan","doi":"10.1109/MMSP.2008.4665214","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665214","url":null,"abstract":"In this paper, we propose a novel approach to speaker diarization of spontaneous meetings in our own multimodal SmartRoom environment. The proposed speaker diarization system first applies a sequential clustering concept to segmentation of a given audio data source, and then performs agglomerative hierarchical clustering for speaker-specific classification (or speaker clustering) of speech segments. The speaker clustering algorithm utilizes an incremental Gaussian mixture cluster modeling strategy, and a stopping point estimation method based on information change rate. Through experiments on various meeting conversation data of approximately 200 minutes total length, this system is demonstrated to provide diarization error rate of 18.90% on average.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133391583","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665188
Bei Na Wei, Yu Shi, G. Ye, Jie Xu
Smart camera system design and implementation is a challenging task due to the constant need to perform computationally demanding image processing tasks with the limited resource constraints of embedded systems. This paper presents the hardware and software co-design and implementation of the first stage of TraffiCam, an FPGA based smart camera prototype for traffic surveillance at intersections, consisting of a CMOS image sensor capture device and FPGA main video processor. In particular, creative solutions for balancing gate array utilization, memory and computation time are presented for the initial stage of Harris keypoint detection with discussions on the algorithm implementation conversions between PC-based to FPGA based platforms. Preliminary results show satisfactory real-time tracking and estimation performance.
{"title":"Developing a smart camera for road traffic surveillance","authors":"Bei Na Wei, Yu Shi, G. Ye, Jie Xu","doi":"10.1109/MMSP.2008.4665188","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665188","url":null,"abstract":"Smart camera system design and implementation is a challenging task due to the constant need to perform computationally demanding image processing tasks with the limited resource constraints of embedded systems. This paper presents the hardware and software co-design and implementation of the first stage of TraffiCam, an FPGA based smart camera prototype for traffic surveillance at intersections, consisting of a CMOS image sensor capture device and FPGA main video processor. In particular, creative solutions for balancing gate array utilization, memory and computation time are presented for the initial stage of Harris keypoint detection with discussions on the algorithm implementation conversions between PC-based to FPGA based platforms. Preliminary results show satisfactory real-time tracking and estimation performance.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116644709","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665039
Xiansheng Hua, Tao Mei, Shipeng Li
The advent of media-sharing sites, especially along with the so called Web 2.0 wave, has led to the unprecedented Internet delivery of community-contributed media contents such as images and videos, which have become the primary sources for online advertising. However, conventional ad-networks such as Google Adwords and AdSense treat image and video advertising as general text advertising by displaying the ads either relevant to the queries or the Web page content, without considering automatically monetizing the rich contents of individual images and videos. In this paper, we summarize the trends of online advertising and propose an innovative advertising model driven by the compelling contents of images and videos. We present recently developed ImageSense and VideoSense as two exemplary applications dedicated to images and videos, respectively, in which the most contextually relevant ads are embedded at the most appropriate positions within the images or videos. The ads are selected based on not only textual relevance but also visual similarity so that the ads yield contextual relevance to both the text in the Web page and the visual content. The ad insertion positions are detected based on visual saliency analysis to minimize the intrusiveness to the user. We also envision that the next trend of multimedia advertising would be game-alike advertising.
{"title":"When multimedia advertising meets the new Internet era","authors":"Xiansheng Hua, Tao Mei, Shipeng Li","doi":"10.1109/MMSP.2008.4665039","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665039","url":null,"abstract":"The advent of media-sharing sites, especially along with the so called Web 2.0 wave, has led to the unprecedented Internet delivery of community-contributed media contents such as images and videos, which have become the primary sources for online advertising. However, conventional ad-networks such as Google Adwords and AdSense treat image and video advertising as general text advertising by displaying the ads either relevant to the queries or the Web page content, without considering automatically monetizing the rich contents of individual images and videos. In this paper, we summarize the trends of online advertising and propose an innovative advertising model driven by the compelling contents of images and videos. We present recently developed ImageSense and VideoSense as two exemplary applications dedicated to images and videos, respectively, in which the most contextually relevant ads are embedded at the most appropriate positions within the images or videos. The ads are selected based on not only textual relevance but also visual similarity so that the ads yield contextual relevance to both the text in the Web page and the visual content. The ad insertion positions are detected based on visual saliency analysis to minimize the intrusiveness to the user. We also envision that the next trend of multimedia advertising would be game-alike advertising.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124658042","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665131
Nannan Ma, H. Xiong, Li Song
This paper aims to attain sparser representation of a 2-D signal by introducing orientation resolution as a second multiresolution besides multiscale, which is formulated to achieve a dual multiresolution decomposition framework by nonuniform directional frequency decompositions (NUDFB) under arbitrary scales. In this scheme, NUDFB is fulfilled by changing the topology structure of a non-symmetric binary tree (NSBT). Through this nonuniform division, we can get arbitrary orientation resolution r at a direction of c2-r under a target scale. Every two-channel filter bank on each node of this NSBT is designed to be a paraunitary perfect reconstruction filter bank, so NUDFB is an orthogonal filter bank. This dual multiresolution decomposition will definitely have bright prospect in its application, such as texture analysis, image processing or video coding. A potential application is presented by applying NUDFB in wavelet domain.
{"title":"2-D dual multiresolution decomposition through NUDFB and its application","authors":"Nannan Ma, H. Xiong, Li Song","doi":"10.1109/MMSP.2008.4665131","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665131","url":null,"abstract":"This paper aims to attain sparser representation of a 2-D signal by introducing orientation resolution as a second multiresolution besides multiscale, which is formulated to achieve a dual multiresolution decomposition framework by nonuniform directional frequency decompositions (NUDFB) under arbitrary scales. In this scheme, NUDFB is fulfilled by changing the topology structure of a non-symmetric binary tree (NSBT). Through this nonuniform division, we can get arbitrary orientation resolution r at a direction of c2-r under a target scale. Every two-channel filter bank on each node of this NSBT is designed to be a paraunitary perfect reconstruction filter bank, so NUDFB is an orthogonal filter bank. This dual multiresolution decomposition will definitely have bright prospect in its application, such as texture analysis, image processing or video coding. A potential application is presented by applying NUDFB in wavelet domain.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128745974","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665111
Xiangjian He, Lihong Zheng, Qiang Wu, W. Jia, B. Samali, M. Palaniswami
License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation.
{"title":"Segmentation of characters on car license plates","authors":"Xiangjian He, Lihong Zheng, Qiang Wu, W. Jia, B. Samali, M. Palaniswami","doi":"10.1109/MMSP.2008.4665111","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665111","url":null,"abstract":"License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129896721","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 : 2008-11-05DOI: 10.1109/MMSP.2008.4665185
Gang Sun, Wei Xing, Dongming Lu
In this paper, we addressed the problem of redundancy allocation for protecting packet loss for better quality of service (QoS) in real-time H.264 video streaming. A novel error-resilient approach is proposed for the transmission of pre-encoded H.264 video stream under bandwidth constrained networks. A novel frame importance model is derived for estimating relative importance index for different H.264 video frames. Combining with the characteristics of the network, the optimal resource allocation strategy for different video frames can be determined for achieving improved error resilience. The model uses frame error propagation index (FEPI) to characterize video quality degradation caused by error propagation in different frames in a GOP when suffer from packet loss. This model can be calculated in DCT domain with the parameters extracted directly from the bitstream. Therefore, the complexity of the proposed scheme is very low and much better for real-time video transmission. Simulation results show that the proposed scheme can improve the receiver side reconstructed video quality remarkably under different channel loss patterns.
{"title":"Low-complexity frame importance modelling and resource allocation scheme for error-resilience H.264 video streaming","authors":"Gang Sun, Wei Xing, Dongming Lu","doi":"10.1109/MMSP.2008.4665185","DOIUrl":"https://doi.org/10.1109/MMSP.2008.4665185","url":null,"abstract":"In this paper, we addressed the problem of redundancy allocation for protecting packet loss for better quality of service (QoS) in real-time H.264 video streaming. A novel error-resilient approach is proposed for the transmission of pre-encoded H.264 video stream under bandwidth constrained networks. A novel frame importance model is derived for estimating relative importance index for different H.264 video frames. Combining with the characteristics of the network, the optimal resource allocation strategy for different video frames can be determined for achieving improved error resilience. The model uses frame error propagation index (FEPI) to characterize video quality degradation caused by error propagation in different frames in a GOP when suffer from packet loss. This model can be calculated in DCT domain with the parameters extracted directly from the bitstream. Therefore, the complexity of the proposed scheme is very low and much better for real-time video transmission. Simulation results show that the proposed scheme can improve the receiver side reconstructed video quality remarkably under different channel loss patterns.","PeriodicalId":402287,"journal":{"name":"2008 IEEE 10th Workshop on Multimedia Signal Processing","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130899045","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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