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2015 Data Compression Conference最新文献

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Subspace Learning with Structured Sparsity for Compressive Video Sampling 压缩视频采样的结构化稀疏子空间学习
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.24
Yong Li, Wenrui Dai, H. Xiong
{"title":"Subspace Learning with Structured Sparsity for Compressive Video Sampling","authors":"Yong Li, Wenrui Dai, H. Xiong","doi":"10.1109/DCC.2015.24","DOIUrl":"https://doi.org/10.1109/DCC.2015.24","url":null,"abstract":"Existing sparse representation with subspace learning is hampered by the intersection of subspaces of bases. With structured sparsity to enable the prior knowledge of signal statistics, this paper proposes a novel compressive video sampling by subspace learning to minimize the intersection of subspaces. As the measurement, the block coherence is optimized with the regularized learning to generate a class of independent bases associated with the subspaces. Thus, the proposed framework can make a compact block sparse representation based on the derived basis in an efficient and adaptive manner. The block-based recovery of video sequences is demonstrated to be stable under the constraint of block restricted isometric property (RIP). Experimental results show that the proposed method outperforms existing compressive video sampling schemes.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128504227","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}
引用次数: 2
Rank Preserving Hashing for Rapid Image Search 基于秩保持哈希的快速图像搜索
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.85
Dongjin Song, W. Liu, David A. Meyer, D. Tao, R. Ji
{"title":"Rank Preserving Hashing for Rapid Image Search","authors":"Dongjin Song, W. Liu, David A. Meyer, D. Tao, R. Ji","doi":"10.1109/DCC.2015.85","DOIUrl":"https://doi.org/10.1109/DCC.2015.85","url":null,"abstract":"In recent years, hashing techniques are becoming overwhelmingly popular for their high efficiency in handling large-scale computer vision applications. It has been shown that hashing techniques which leverage supervised information can significantly enhance performance, and thus greatly benefit visual search tasks. Typically, a modern hashing method uses a set of hash functions to compress data samples into compact binary codes. However, few methods have developed hash functions to optimize the precision at the top of a ranking list based upon Hamming distances. In this paper, we propose a novel supervised hashing approach, namely Rank Preserving Hashing (RPH), to explicitly optimize the precision of Hamming distance ranking towards preserving the supervised rank information. The core idea is to train disciplined hash functions in which the mistakes at the top of a Hamming-distance ranking list are penalized more than those at the bottom. To find such hash functions, we relax the original discrete optimization objective to a continuous surrogate, and then design an online learning algorithm to efficiently optimize the surrogate objective. Empirical studies based upon two benchmark image datasets demonstrate that the proposed hashing approach achieves superior image search accuracy over the state-of-the-art approaches.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133076799","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}
引用次数: 20
Serializing RDF in Compressed Space 在压缩空间中序列化RDF
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.16
Antonio Hernández-Illera, Miguel A. Martínez-Prieto, Javier D. Fernández
{"title":"Serializing RDF in Compressed Space","authors":"Antonio Hernández-Illera, Miguel A. Martínez-Prieto, Javier D. Fernández","doi":"10.1109/DCC.2015.16","DOIUrl":"https://doi.org/10.1109/DCC.2015.16","url":null,"abstract":"The amount of generated RDF data has grown impressively over the last decade, promoting compression as an essential tool for storage and exchange. RDF compression techniques leverage syntactic and semantic redundancies, but structural repetitions are not always addressed effectively. This paper first shows two schema-based sources of redundancy underlying to the schema-relaxed nature of RDF. Then, we revisit the W3C HDT binary format to further compact its graph structure encoding. Our HDT++ approach reduces the original HDT Triples requirements up to 2 times for more structured datasets, and reports significant improvements even for highly semi-structured datasets like DBpedia. In general, HDT++ competes with the current state of the art for structural RDF compression, leading the comparison for three of the four analyzed datasets.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123866221","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}
引用次数: 19
Improving PPM with Dynamic Parameter Updates 通过动态参数更新改进PPM
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.77
Christian Steinruecken, Zoubin Ghahramani, D. MacKay
{"title":"Improving PPM with Dynamic Parameter Updates","authors":"Christian Steinruecken, Zoubin Ghahramani, D. MacKay","doi":"10.1109/DCC.2015.77","DOIUrl":"https://doi.org/10.1109/DCC.2015.77","url":null,"abstract":"This article makes several improvements to the classic PPM algorithm, resulting in a new algorithm with superior compression effectiveness on human text. The key differences of our algorithm to classic PPM are that (A) rather than the original escape mechanism, we use a generalised blending method with explicit hyper-parameters that control the way symbol counts are combined to form predictions, (B) different hyper-parameters are used for classes of different contexts, and (C) these hyper-parameters are updated dynamically using gradient information. The resulting algorithm (PPM-DP) compresses human text better than all currently published variants of PPM, CTW, DMC, LZ, CSE and BWT, with runtime only slightly slower than classic PPM.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129152608","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}
引用次数: 5
Compound-Cognizant Feature Compression of Gas Chromatographic Data to Facilitate Environmental Forensics 气相色谱数据的化合物识别特征压缩以促进环境取证
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.73
H. G. Damavandi, A. Gupta, C. Reddy, Robert Nelson
{"title":"Compound-Cognizant Feature Compression of Gas Chromatographic Data to Facilitate Environmental Forensics","authors":"H. G. Damavandi, A. Gupta, C. Reddy, Robert Nelson","doi":"10.1109/DCC.2015.73","DOIUrl":"https://doi.org/10.1109/DCC.2015.73","url":null,"abstract":"We present complementary compound-cognizant data engineering techniques for feature compression and data indexing across two-dimensional gas chromatographic (GC×GC) datasets with petroleum forensics as the primary application. We propose single-linkage clustering of dominant compounds (targets) along with local interpretation across biomarker peak profiles. Our methods enable high-volume data compression, along with robust querying and forensic distinction between similar sources. We validate our techniques against a diverse dataset of thirty-four crude oil injections collected from nineteen distinct sources across the planet, with emphasis on Macon do well, the source of Deepwater Horizon disaster (Gulf of Mexico, April 2010).","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124420368","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}
引用次数: 4
Multi-stage Hash Based Motion Estimation for HEVC 基于多阶段哈希的HEVC运动估计
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.25
Weijia Zhu, Wenpeng Ding, Jizheng Xu, Yunhui Shi, Baocai Yin
{"title":"Multi-stage Hash Based Motion Estimation for HEVC","authors":"Weijia Zhu, Wenpeng Ding, Jizheng Xu, Yunhui Shi, Baocai Yin","doi":"10.1109/DCC.2015.25","DOIUrl":"https://doi.org/10.1109/DCC.2015.25","url":null,"abstract":"Motion estimation plays an important role in video coding standards, such as H.264/AVC and HEVC. In this paper, we propose a multi-stage hash based motion estimation algorithm for HEVC, which enables hash based motion estimation for natural videos. In the proposed method, the prediction blocks significantly different from the current prediction unit will be eliminated in the motion estimation process. Locality sensitive hashing functions are used to measure the difference between the input block and predicted blocks. The proposed algorithm is implemented into the HM 12.0 software, and the simulation results show that the complexity of motion estimation is significantly reduced with negligible coding performance loss.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114391192","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}
引用次数: 0
Practical Compression with Model-Code Separation 模型-代码分离的实用压缩
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.80
Ying-zong Huang, G. Wornell
{"title":"Practical Compression with Model-Code Separation","authors":"Ying-zong Huang, G. Wornell","doi":"10.1109/DCC.2015.80","DOIUrl":"https://doi.org/10.1109/DCC.2015.80","url":null,"abstract":"Current compression systems incorporate a data model, however formed, deeply into the coding process, leading to difficulties of an architectural nature. This work contributes an alternative \"Model-Code Separation\" architecture for general compression, based on model-free coding and iterative message-passing algorithms over graphical models representing the modeling and coding aspects of compression in decoding. Systems following this architecture resolve important challenges posed by current systems, and stand to benefit further from advances in the understanding of data and the algorithms that process them.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115151977","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}
引用次数: 0
Variable-Length Lossy Compression Algorithms Based on Constrained Random Numbers 基于约束随机数的变长有损压缩算法
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.45
J. Muramatsu
{"title":"Variable-Length Lossy Compression Algorithms Based on Constrained Random Numbers","authors":"J. Muramatsu","doi":"10.1109/DCC.2015.45","DOIUrl":"https://doi.org/10.1109/DCC.2015.45","url":null,"abstract":"Summary form only given. A variable-length lossy compression algorithms for a stationary memory less source with a continuous alphabet are introduced with a rate-distortion pair close to the rate-distortion function.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"312 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115561598","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}
引用次数: 0
A Data-Driven Probabilistic CTU Splitting Algorithm for Fast H.264/HEVC Video Transcoding H.264/HEVC视频快速转码的数据驱动概率CTU分割算法
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.46
A. J. Díaz-Honrubia, José Luis Martínez, P. Cuenca, J. A. Gamez, J. M. Puerta
{"title":"A Data-Driven Probabilistic CTU Splitting Algorithm for Fast H.264/HEVC Video Transcoding","authors":"A. J. Díaz-Honrubia, José Luis Martínez, P. Cuenca, J. A. Gamez, J. M. Puerta","doi":"10.1109/DCC.2015.46","DOIUrl":"https://doi.org/10.1109/DCC.2015.46","url":null,"abstract":"High Efficiency Video Coding was developed by the JCT-VC to replace the current H.264/AVC standard, which has dominated digital video services in all segments of the domestic and professional markets for over ten years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient video transcoding from H.264 to HEVC will be needed to enable gradual migration to HEVC. HEVC adopts a quad tree-based Coding Unit block partitioning structure that is flexible in adapting various texture characteristics at the expense of a high computational cost. This paper presents a data-driven probabilistic CTU splitting algorithm that is designed to exploit the information gathered at the H.264/AVC decoder in order to make faster decisions on CU splitting in HEVC. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder, and, moreover, it outperforms other related works available in the literature.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125389973","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}
引用次数: 5
Depth Error Induced Virtual View Synthesis Distortion Estimation for 3D Video Coding 基于深度误差的三维视频编码虚拟视图综合失真估计
2015 Data Compression Conference Pub Date : 2015-04-07 DOI: 10.1109/DCC.2015.10
Yijian Xiang, Lu Fang, Ren Li, Ngai-Man Cheung
{"title":"Depth Error Induced Virtual View Synthesis Distortion Estimation for 3D Video Coding","authors":"Yijian Xiang, Lu Fang, Ren Li, Ngai-Man Cheung","doi":"10.1109/DCC.2015.10","DOIUrl":"https://doi.org/10.1109/DCC.2015.10","url":null,"abstract":"We propose an analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking into account the configuration of the cameras. Focusing on view synthesis under depth error, we carefully analyze the merging operations under different situations that affect pixel availability: overlapping region, disocclusion and boundary region, disparity error region, and infrequent region. The analysis leads to quadratic/biquadratic models and linear models that explicitly relate the distance between camera positions (reference/virtual view) to Distortion under Different Situations (DDS) and Probability under Different Situations (PDS), respectively. We also show that VVSD is the linear combination of DDS weighted by PDS. Our careful analysis results in state-of-the-art estimation accuracy. Experimental results verify that the proposed model is capable to produce accurate estimates of VVSD based on the distance between reference/virtual views. Therefore, our model can effectively inform camera setup for capturing, in particular, the set-up of the cameras in situation where depth information will be compressed subsequently.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128579686","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}
引用次数: 1
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