2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)最新文献_第9页

View synthesis for 3D video scene composition 查看合成的3D视频场景组成

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340824

Amanda Wang, Chun-Liang Chien, H. Hang

引用次数: 0

Rectangle fitting via quadratic programming 二次规划矩形拟合

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340875

Jingyu Yang, Zhongyu Jiang

引用次数: 6

Epipolar plane image based rendering for 3D video coding 基于极平面图像的三维视频编码渲染

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340854

Catarina Brites, J. Ascenso, F. Pereira

{"title":"Epipolar plane image based rendering for 3D video coding","authors":"Catarina Brites, J. Ascenso, F. Pereira","doi":"10.1109/MMSP.2015.7340854","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340854","url":null,"abstract":"In current 3D video coding solutions, such as the 3D-HEVC standard, depth data is instrumental to have a continuum of views synthesized at the decoder based on a limited set of coded views. In order view synthesis may be performed at the decoder, depth data is currently directly acquired or estimated at the encoder based on very few neighboring views and transmitted to the decoder after appropriate compression. At the decoder, further views then those decoded are synthesized using again very few neighboring decoded views, thus using a local synthesis approach. A promising alternative synthesis approach may consider not a few but rather all the views available at the decoder, thus offering a scene global approach to synthesis. One way to implement this approach involves cutting the views cube along the viewpoint direction, creating the so-called epipolar plane images (EPI) which provide a rather compact representation of the scene. In this context, this paper proposes an EPI based view rendering framework for 3D video coding solution and identifies the major benefits of such framework, notably in comparison with the traditional local synthesis approach.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121415630","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

Non-invasive imaging based on sparse representation 基于稀疏表示的无创成像

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340865

K. Wei, Xin Jin, Yifu Hu, Qionghai Dai

引用次数: 0

Multi-rate encoding for HEVC-based adaptive HTTP streaming with multiple resolutions 基于hevc的多分辨率自适应HTTP流的多速率编码

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340822

Damien Schroeder, Adithyan Ilangovan, E. Steinbach

引用次数: 7

Human action recognition using temporal hierarchical pyramid of depth motion map and KECA 基于时间层次金字塔深度运动图和kea的人体动作识别

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340857

Nour El-Din El-Madany, Yifeng He, L. Guan

引用次数: 12

Scalable logo recognition based on compact sparse dictionary for mobile devices 基于紧凑稀疏字典的移动设备可扩展标识识别

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340863

Sheng Tang, Yongdong Zhang, Hui Chen

{"title":"Scalable logo recognition based on compact sparse dictionary for mobile devices","authors":"Sheng Tang, Yongdong Zhang, Hui Chen","doi":"10.1109/MMSP.2015.7340863","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340863","url":null,"abstract":"In this paper, we present a novel scalable logo recognition system which can recognize a large number of logo categories locally on mobile devices. The system is unsupervised without any supervised training procedure, and very time efficient at low memory cost. It is also robust against challenging conditions such as noise addition, different image scale, rotation, etc. To achieve this goal, we propose an efficient segmental quantization approach for generation of large visual words over one million size with a very compact vocabulary. The vocabulary consists of two small dictionaries learned through sparse non-negative matrix factorization (NMF) of local SIFT descriptors. With an inverted index structure built through the large visual words, query images containing logos can be recognized through efficient retrieval of K-nearest neighbors (K-NN) of logo instances in the dataset. Our vocabulary size is very small, only one thousandth of that of traditional Approximate K-Means (AKM) method, which is of great importance for mobile devices with limited memory. Furthermore, based on the compact dictionary, we present a promising verification way of filtering false positives via sparse reconstruction of SIFT descriptors with a very few number of sparse codes due to the sparsity's property of lowest reconstruction error. Experiments on our dataset with 400 logo classes show that our system is very efficient and effective.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131407695","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

Contrast and distribution based saliency detection in infrared images 基于对比度和分布的红外图像显著性检测

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340825

Lu Li, Yu Zheng, F. Zhou

引用次数: 4

Visual summarization for place-of-interest by social-contextual constrained geo-clustering 基于社会语境约束的地理聚类的景点视觉摘要

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340837

Yayun Ren, Xueming Qian, Shuhui Jiang

{"title":"Visual summarization for place-of-interest by social-contextual constrained geo-clustering","authors":"Yayun Ren, Xueming Qian, Shuhui Jiang","doi":"10.1109/MMSP.2015.7340837","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340837","url":null,"abstract":"With the rapid development of social networks, more and more users choose to share their own photos with their friends. Especially, users prefer to share the photos they took during traveling, thus there emerges many user generated content for place-of-interests (POIs). So based on the user contributed photos, we can summarize each POI by mining location-of-interest (LOI, which represents the attractive viewpoints of POI) and selecting some representative images from them. It is important for scheduling a traveling, and in this paper, an effective POI summarization approach is proposed by an improved geo-clustering with visual and views verification, which helps us to have a representative and comprehensive perception for POI. In our approach, we firstly collect POI related photos from social media, and filter the raw data by the combination of tags and geo-locations. Secondly, we mine LOIs for each POI by the improved geo-location clustering method. Finally, we employ visual and views verification to select images from LOIs to summarize the POI. We conduct a series of experiments based on Flcoickr dataset. Experimental results demonstrate the effectiveness of our proposed method.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114216013","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

Contour approximation & depth image coding for virtual view synthesis 面向虚拟视图合成的轮廓逼近与深度图像编码

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-10-01 DOI: 10.1109/MMSP.2015.7340855

Yuan Yuan, Gene Cheung, P. Frossard, P. Callet, H. V. Zhao

{"title":"Contour approximation & depth image coding for virtual view synthesis","authors":"Yuan Yuan, Gene Cheung, P. Frossard, P. Callet, H. V. Zhao","doi":"10.1109/MMSP.2015.7340855","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340855","url":null,"abstract":"A depth image provides geometric information of a 3D scene, namely the shapes of physical objects captured from a particular viewpoint. This information is important for synthesizing images corresponding to different virtual camera viewpoints via depth-image-based rendering (DIBR). Since it has been shown that blurring of object contours in the depth images leads to bleeding artefacts in virtual images. The most effective way to compress depth images relies on edge-adaptive image codecs that preserve contours, which are losslessly coded as side information (SI). However, lossless coding of the exact object contours can be expensive. In this paper, we argue that the contours themselves can be suitably approximated to save bits, while the depth images piecewise smooth (PWS) characteristic stays preserved. Specifically, we first propose a metric that estimates contour coding rate based on edge statistics. Given an initial rate estimate, we then pro-actively approximate object contours in a way that guarantees rate reduction when coded using arithmetic edge coding (AEC) as SI. Given the sharp but approximated contours, we finally encode the image using an edge-adaptive image codec with graph Fourier transform (GFT) for edge preservation. We show in our experiments that by maintaining sharp but slightly inaccurate object contours, the resulting quality of virtual views synthesized via DIBR exceeds those synthesized using depth images compressed with edge-adaptive codecs that losslessly encode object contours as SI, in particular when the total coding rate budget is low. This confirms that optimized coding of depth images results in an effective tradeoff in the representation of contour and respective depth information.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122562457","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