2017 IEEE International Conference on Multimedia and Expo (ICME)最新文献_第3页

The OUC-vision large-scale underwater image database OUC-vision大型水下图像数据库

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019324

Muwei Jian, Qiang Qi, Junyu Dong, Yinlong Yin, Wenyin Zhang, K. Lam

{"title":"The OUC-vision large-scale underwater image database","authors":"Muwei Jian, Qiang Qi, Junyu Dong, Yinlong Yin, Wenyin Zhang, K. Lam","doi":"10.1109/ICME.2017.8019324","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019324","url":null,"abstract":"In this paper, a large-scale underwater image database for underwater salient object detection or saliency detection is presented in detail. This database is called the OUC-VISION underwater image database, which contains 4400 underwater images of 220 individual objects. Each object is captured with four pose variations (the frontal-, the opposite-, the left-, and the right-views of each underwater object) and five spatial locations (the underwater object is located at the top-left corner, the top-right corner, the center, the bottom-left corner, and the bottom-right corner) to obtain 20 images. Meanwhile, this publicly available OUC-VISION database also provides relevant industrial fields, and academic researchers with underwater images under different sources of variations, especially pose, spatial location, illumination, turbidity of water, etc. Ground-truth information is also manually labelled for this database. The OUC-VISION database can not only be widely used to assess and evaluate the performance of the state-of-the-art salient-object detection and saliency-detection algorithms for general images, but also will particularly benefit the development of underwater vision technology in the future.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125264697","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: 33

Fast 3D point cloud segmentation using supervoxels with geometry and color for 3D scene understanding 快速3D点云分割使用超体素与几何和颜色的3D场景的理解

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019382

Francesco Verdoja, D. Thomas, A. Sugimoto

引用次数: 37

Toward the realization of six degrees-of-freedom with compressed light fields 朝着实现六自由度压缩光场的方向发展

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019543

A. Hinds, D. Doyen, P. Carballeira

{"title":"Toward the realization of six degrees-of-freedom with compressed light fields","authors":"A. Hinds, D. Doyen, P. Carballeira","doi":"10.1109/ICME.2017.8019543","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019543","url":null,"abstract":"360° video, supporting the ability to present views consistent with the rotation of the viewer's head along three axes (roll, pitch, yaw) is the current approach for creation of immersive video experiences. Nevertheless, a more fully natural, photorealistic experience — with support of visual cues that facilitate coherent psycho-visual sensory fusion without the side-effect of cyber-sickness — is desired. 360° video applications that additionally enable the user to translate in x, y, and z directions are clearly a subsequent frontier to be realized toward the goal of sensory fusion without cyber-sickness. Such support of full Six Degrees-of-Freedom (6 DoF) for next generation immersive video is a natural application for light fields. However, a significant obstacle to the adoption of light field technologies is the large data necessary to ensure that the light rays corresponding to the viewer's position relative to 6-DoF are properly delivered, either from captured light information or synthesized from available views. Experiments to improve known methods for view synthesis and depth estimation are therefore a fundamental next step to establish a reference framework within which compression technologies can be evaluated. This paper describes a testbed and experiments to enable smooth and artefact-free view transitions that can later be used in a framework to study how best to compress the data.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123136048","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: 13

Deep convolutional recurrent neural network with attention mechanism for robust speech emotion recognition 基于注意机制的深度卷积递归神经网络鲁棒语音情感识别

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019296

Che-Wei Huang, Shrikanth S. Narayanan

引用次数: 101

Perceptual quality assessment of 3D synthesized images 三维合成图像的感知质量评价

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019307

M. S. Farid, M. Lucenteforte, Marco Grangetto

{"title":"Perceptual quality assessment of 3D synthesized images","authors":"M. S. Farid, M. Lucenteforte, Marco Grangetto","doi":"10.1109/ICME.2017.8019307","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019307","url":null,"abstract":"Multiview video plus depth (MVD) is the most popular 3D video format where the texture images contain the color information and the depth maps represent the geometry of the scene. The depth maps are exploited to obtain intermediate views to enable 3D-TV and free-viewpoint applications using the depth image based rendering (DIBR) techniques. DIBR is used to get an estimate of the intermediate views but has to cope with depth errors, occlusions, imprecise camera parameters, re-interpolation, to mention a few issues. Therefore, being able to evaluate the true perceptual quality of synthesized images is of paramount importance for a high quality 3D experience. In this paper, we present a novel algorithm to assess the quality of the synthesized images in the absence of the corresponding references. The algorithm uses the original views from which the virtual image is generated to estimate the distortion induced by the DIBR process. In particular, a block-based perceptual feature matching based on signal phase congruency metric is devised to estimate the synthesis distortion. The experiments worked out on standard DIBR synthesized database show that the proposed algorithm achieves high correlation with the subjective ratings and outperforms the existing 3D quality assessment algorithms.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":"24 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131171582","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: 17

Large-scale person re-identification as retrieval 作为检索的大规模人物再识别

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019485

Hantao Yao, Shiliang Zhang, Dongming Zhang, Yongdong Zhang, Jintao Li, Yu Wang, Q. Tian

{"title":"Large-scale person re-identification as retrieval","authors":"Hantao Yao, Shiliang Zhang, Dongming Zhang, Yongdong Zhang, Jintao Li, Yu Wang, Q. Tian","doi":"10.1109/ICME.2017.8019485","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019485","url":null,"abstract":"This paper targets to bring together the research efforts on two fields that are growing actively in the past few years: multicamera person Re-Identification (ReID) and large-scale image retrieval. We demonstrate that the essentials of image retrieval and person ReID are the same, i.e., measuring the similarity between images. However, person ReID requires more discriminative and robust features to identify the subtle differences of different persons and overcome the large variance among images of the same person. Specifically, we propose a coarse-to-fine (C2F) framework and a Convolutional Neural Network structure named as Conv-Net to tackle the large-scale person ReID as an image retrieval task. Given a query person image, the C2F firstly employ Conv-Net to extract a compact descriptor and perform the coarse-level search. A robust descriptor conveying more spatial cues is hence extracted to perform the fine-level search. Extensive experimental results show that the proposed method outperforms existing methods on two public datasets. Further, the evaluation on a large-scale Person-520K dataset demonstrates that our work is significantly more efficient than existing works, e.g., only needs 180ms to identify a query person from 520K images.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":"17 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131352880","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: 25

Decoder-side HEVC quality enhancement with scalable convolutional neural network 基于可扩展卷积神经网络的解码器侧HEVC质量增强

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019299

Ren Yang, Mai Xu, Zulin Wang

引用次数: 95

Blind proposal quality assessment via deep objectness representation and local linear regression 基于深度客观表征和局部线性回归的盲提案质量评价

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019305

Q. Wu, Hongliang Li, Fanman Meng, K. Ngan, Linfeng Xu

引用次数: 3

Partially occluded facial action recognition and interaction in virtual reality applications 虚拟现实应用中部分遮挡面部动作识别与交互

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019545

U. Ciftci, Xing Zhang, Lijun Tin

引用次数: 11

Improving acoustic modeling using audio-visual speech 利用视听语音改进声学建模

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-10 DOI: 10.1109/ICME.2017.8019294

A. H. Abdelaziz

引用次数: 5