2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)最新文献_第4页

Traffic flow matching with clique and triplet cues 交通流量匹配的派系和三重线索

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340792

Lihang Liu, Weiyao Lin, Youping Zhong

引用次数: 4

Large scale multi-class classification using latent classifiers 基于潜在分类器的大规模多类分类

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340800

Tien-Dung Mai, T. Ngo, Duy-Dinh Le, D. Duong, Kiem Hoang, S. Satoh

引用次数: 0

Combining deep learning and unsupervised clustering to improve scene recognition performance 结合深度学习和无监督聚类提高场景识别性能

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340859

Armin Kappeler, R. Morris, Amar Ramesh Kamat, Nikhil Rasiwasia, Gaurav Aggarwal

引用次数: 3

Hidden target detection from the multi-echo small-footprint LiDAR point clouds 基于多回波小足迹激光雷达点云的隐藏目标检测

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340880

Yiping Chen, Cheng Wang, Jonathan Li

{"title":"Hidden target detection from the multi-echo small-footprint LiDAR point clouds","authors":"Yiping Chen, Cheng Wang, Jonathan Li","doi":"10.1109/MMSP.2015.7340880","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340880","url":null,"abstract":"We propose a new approach for hidden or potential object detection behind the vegetation based on the multi-echo small-footprint of light detection and ranging(LiDAR) point cloud. According to the specific characteristic that laser beam is able to penetrate foliage gaps, which offers the opportunity to perceive and detect the object invisible to the naked eye. First, the waveform sample data of the small footprint multi-echo liDAR uses a Gaussian fitting tool to curve fitting. Second, the peak detection of the waveform can be classified in statistical results of its wave numbers. Decomposition and correction are the processing for classifying based on the statistic data. After selecting the point clouds which are contained in the multi-peaks echoes, we obtain the tree and the embedded target behind it as well as ground elimination. The range of the waveform component is used to separate the penetrations material and the target by distance discriminant function. Experiments are implemented on the waveforms acquired by small-footprint LiDAR system VZ-1000 Sensor. The results indicate that the algorithm could provide an optimal solution for LiDAR waveform hidden target detection.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"40 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133159753","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

Learning-based movie summarization via role-community analysis and feature fusion 基于角色社区分析和特征融合的基于学习的电影总结

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340794

Jun-Ying Li, Li-Wei Kang, Chia-Ming Tsai, Chia-Wen Lin

{"title":"Learning-based movie summarization via role-community analysis and feature fusion","authors":"Jun-Ying Li, Li-Wei Kang, Chia-Ming Tsai, Chia-Wen Lin","doi":"10.1109/MMSP.2015.7340794","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340794","url":null,"abstract":"Movie summarization aims at condensing a full-length movie to a significantly shortened version that still preserves the movie's major semantic content. In this paper, we propose a learning-based movie summarization framework via role-community social network analysis and feature fusion. In our framework, scene-based movie summarization is formulated as a 0-1 knapsack problem, where the scene attention value for each significant scene is calculated as its “value” and the length of this scene is used as its “cost.” To identify the significance of each scene, we propose a learning-based approach to fuse the information derived from visual saliency (based on low-level features and high-level cognitive process for an input movie), high-level semantic analysis (based on the global and local social networks constructed from the movie), and user preferences. Our evaluation results show that in most test cases, the proposed method subjectively outperforms attention-based and role-based summarization methods and our previous role-community-based method in terms of semantic content preservation.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128276596","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: 8

Rotation invariant ellipsoid projection for domain transfer in human skin detection 旋转不变椭球投影在人体皮肤检测中的域转移

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340810

Jie Geng, Z. Miao, Qinghua Liang, Shu Wang

引用次数: 1

Spatio-Temporal Pyramid Model based on depth maps for action recognition 基于深度图的时空金字塔模型动作识别

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340806

Haining Xu, E. Chen, Chengwu Liang, L. Qi, L. Guan

引用次数: 19

A fast region-level 3D-warping method for depth-image-based rendering 基于深度图像渲染的快速区域级3d翘曲方法

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340819

Jian Jin, Anhong Wang, Yao Zhao, Chunyu Lin

引用次数: 0

A two-stage fast CU size decision method for HEVC intracoding HEVC内编码的两阶段快速CU大小决策方法

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340816

Qi Zhang, Jun Sun, Y. Duan, Zongming Guo

{"title":"A two-stage fast CU size decision method for HEVC intracoding","authors":"Qi Zhang, Jun Sun, Y. Duan, Zongming Guo","doi":"10.1109/MMSP.2015.7340816","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340816","url":null,"abstract":"In HEVC coding standard, the encoder employs a quad-tree-based Coding Unit (CU) structure to adapt to various texture characteristics of images. Although it provides better compression performance, the computation load increases drastically. In this paper, a two-stage fast CU size decision method is proposed for HEVC intra coding. In the first stage, we utilize the combination of the weighted variance and the maximum value of the Hadamard costs of the four sub CUs to represent the CU complexity, and classify each CU into three categories: compound, homogeneous, and undetermined. The former two kinds of CUs will be made early split and pruned decisions respectively. In the second stage, an improved SATD-based estimated R-D cost is employed to decide whether the prev undetermined CUs should be early pruned. Experimental results demonstrate that compared with the reference software HM13.0, the proposed fast CU size decision method provides 49% time reduction with slight quality degradation using the HEVC all intra test condition. This proposal has been adopted to provide HEVC video and picture encoding services at the server-side for UC mobile browser which covers over 100 million people in China.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116124900","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: 10

An evaluation criterion of saliency models for video seam carving 视频缝刻显著性模型的评价标准

2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2015-12-03 DOI: 10.1109/MMSP.2015.7340841

M. Decombas, Pierre Marighetto, M. Mancas, Ioannis Cassagne, Nicolas Riche, B. Gosselin, T. Dutoit, R. Laganière

{"title":"An evaluation criterion of saliency models for video seam carving","authors":"M. Decombas, Pierre Marighetto, M. Mancas, Ioannis Cassagne, Nicolas Riche, B. Gosselin, T. Dutoit, R. Laganière","doi":"10.1109/MMSP.2015.7340841","DOIUrl":"https://doi.org/10.1109/MMSP.2015.7340841","url":null,"abstract":"Modeling human attention has been arousing a lot of interest due to its numerous applications. The process that allows us to focus on some more important stimuli is defined as the “attention”. Seam carving is an approach to resize images or video sequences while preserving the semantic content. To define what is important, gradient was first used but due to limitations of this approach, saliency models, which are able to predict whether regions in the images attract human attention, are now used. Most of them are optimized to conform a ground truth like eye tracking but there is no way to know the efficiency of the saliency models applied in a specific application like in seam carving. In this paper, we propose a criterion, based on the quantity of geometric deformation and the image's reduction, which evaluate the quality of a resizing by seam carving. This criterion is applied on evaluation of image (SCES) or video (SCED) resizing. We validate our criterion with subjective evaluation and used it to rank state of the art saliency models for seam carving. Evaluation of the image by SCES gives a Spearman correlation of -0.92196 and a Pearson correlation of -0.8812. For the video, the final SCED gives a Spearman correlation of -0.81351 and a Pearson correlation of -0.80581.","PeriodicalId":108577,"journal":{"name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125918713","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