2018 IEEE International Symposium on Multimedia (ISM)最新文献_第2页

Effect of Number of Stimuli on Users Perception of Different Speech Degradations. A Crowdsourcing Case Study 刺激数对不同语音退化用户感知的影响。众包案例研究

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00-16

Rafael Zequeira Jiménez, Gabriel Mittag, S. Möller

{"title":"Effect of Number of Stimuli on Users Perception of Different Speech Degradations. A Crowdsourcing Case Study","authors":"Rafael Zequeira Jiménez, Gabriel Mittag, S. Möller","doi":"10.1109/ISM.2018.00-16","DOIUrl":"https://doi.org/10.1109/ISM.2018.00-16","url":null,"abstract":"Crowdsourcing (CS) has established as a powerful tool to collect human input for data acquisition and labeling. However, it remains the question about the validity of the data collected in a CS platform. Sometimes, the users work carelessly or they try to tweak the system to maximize their profits. This paper reports on whether the number of speech stimuli presented to the listeners has an impact on the user perception of certain degradation conditions applied to the speech signal. To this end, a crowdsourcing study has been conducted with 209 listeners that were divided in three non-overlapping user groups, each of which was presented with tasks containing a different number of stimuli: 10, 20, or 40. Listeners were asked to rate speech stimuli with respect to their overall quality and the ratings were collected on a 5-point scale in accordance with ITU-T Rec. P.800. Workers assessed the speech stimuli of the database 501 from ITU-T Rec. P.863. Additionally, the influence of certain speech signal characteristics, such as interruptions and bandwidth, on the quality perception of the workers was investigated.","PeriodicalId":308698,"journal":{"name":"2018 IEEE International Symposium on Multimedia (ISM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115912284","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

Deep Reinforcement Learning with Parameterized Action Space for Object Detection 基于参数化动作空间的深度强化学习用于目标检测

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00025

Zheng Wu, N. Khan, Lei Gao, L. Guan

引用次数: 14

3D Convolutional Network Based Foreground Feature Fusion 基于三维卷积网络的前景特征融合

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00036

Hanjian Song, Lihua Tian, Chen Li

引用次数: 2

Mobile Scanner for Protein Crystallization Plates 蛋白质结晶板移动扫描仪

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.000-5

Ashok Shrestha, Truong X. Tran, R. S. Aygün, M. Pusey

{"title":"Mobile Scanner for Protein Crystallization Plates","authors":"Ashok Shrestha, Truong X. Tran, R. S. Aygün, M. Pusey","doi":"10.1109/ISM.2018.000-5","DOIUrl":"https://doi.org/10.1109/ISM.2018.000-5","url":null,"abstract":"Protein crystallization well plate is a rectangular platform that contains wells usually organized as a grid structure. The crystallization conditions are studied through a screening process by setting up the trial conditions in the well plate. In the past, the expert evaluates the trial wells for the growth of crystals by manually viewing the plate under a microscope or using a high-throughput plate imaging and analysis system. While the first method is tedious and cumbersome, the second method requires financial investment. Recently, a few approaches were developed by collecting images using smartphones thus enabling low-cost automatic scoring (classification) of well images. Nevertheless, these recent methods do not detect which well on the plate is captured. If the user has a smartphone, the user may capture or scan any well by just moving the smartphone to the corresponding well. In this paper, we propose a mobile scanner that identifies the well by using a coded template under the well plate. The mobile scanner provides two modes: image and video. Image mode is used for single well analysis whereas video mode is used to scan the complete plate. In the video mode, the mobile scanner app generates a tilemap of the plate.","PeriodicalId":308698,"journal":{"name":"2018 IEEE International Symposium on Multimedia (ISM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131492579","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

Acoustic Scene Classification Using Reduced MobileNet Architecture 基于简化MobileNet架构的声学场景分类

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00038

Jun-Xiang Xu, Tzu-Ching Lin, Tsai-Ching Yu, Tzu-Chiang Tai, P. Chang

{"title":"Acoustic Scene Classification Using Reduced MobileNet Architecture","authors":"Jun-Xiang Xu, Tzu-Ching Lin, Tsai-Ching Yu, Tzu-Chiang Tai, P. Chang","doi":"10.1109/ISM.2018.00038","DOIUrl":"https://doi.org/10.1109/ISM.2018.00038","url":null,"abstract":"Sounds are ubiquitous in our daily lives, for instance, sounds of vehicles or sounds of conversations between people. Therefore, it is easy to collect all these soundtracks and categorize them into different groups. By doing so, we can use these assets to recognize the scene. Acoustic scene classification allows us to do so by training our machine which can further be installed on devices such as smartphones. This provides people with convenience which improves our lives. Our goal is to maximize our validation rate of our machine learning results and also optimize our usage of hardware. We utilize the dataset from IEEE Detection and Classification of Acoustic Scenes and Events (DCASE) to train our machine. The data of DCASE 2017 contains 15 different kinds of outdoor audio recordings, including beach, bus, restaurant etc. In this work, we use two different types of signal processing techniques which are Log Mel and HPSS (Harmonic-Percussive Sound Separation). Next we modify and reduce the MobileNet structure to train our dataset. We also make use of fine-tuning and late fusion to make our results more accurate and to improve our performances. With the structure aforementioned, we succeed in reaching the validation rate of 75.99% which is approximately the seventh highest performing group of the Detection and Classification of Acoustic Scenes and Events (DCASE) Challenge 2017, with less computational complexity comparing with others having higher accuracy. We deem it a worthy trade-off.","PeriodicalId":308698,"journal":{"name":"2018 IEEE International Symposium on Multimedia (ISM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130030571","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: 6

[Copyright notice] (版权)

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ism.2018.00003

引用次数: 0

Live Demonstration: Kvazzup 4K HEVC Video Call 现场演示:Kvazzup 4K HEVC视频通话

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00-13

Joni Rasanen, Marko Viitanen, Jarno Vanne, T. Hämäläinen

引用次数: 0

Discriminative Robust Gaze Estimation Using Kernel-DMCCA Fusion 基于核- dmcca融合的判别鲁棒凝视估计

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00064

Salah Rabba, M. Kyan, Lei Gao, A. Quddus, A. S. Zandi, L. Guan

{"title":"Discriminative Robust Gaze Estimation Using Kernel-DMCCA Fusion","authors":"Salah Rabba, M. Kyan, Lei Gao, A. Quddus, A. S. Zandi, L. Guan","doi":"10.1109/ISM.2018.00064","DOIUrl":"https://doi.org/10.1109/ISM.2018.00064","url":null,"abstract":"The proposed framework employs discriminative analysis for gaze estimation using kernel discriminative multiple canonical correlation analysis (K-DMCCA), which represents different feature vectors that account for variations of head pose, illumination and occlusion. The feature extraction component of the framework includes spatial indexing, statistical and geometrical elements. Gaze estimation is constructed by feature aggregation and transforming features into a higher dimensional space using the RBF kernel �� and spread factor. The output of fused features through K-DMCCA is robust to illumination, occlusion and is calibration free. Our algorithm is validated on MPII, CAVE, ACS and EYEDIAP datasets. The two main contributions of the framework are the following: Enhancing the performance of DMCCA with the kernel and introducing quadtree as an iris region descriptor. Spatial indexing using quadtree is a robust method for detecting which quadrant the iris is situated, detecting the iris boundary and it is inclusive of statistical and geometrical indexing that are calibration free. Our method achieved an accurate gaze estimation of 4.8º using Cave, 4.6° using MPII, 5.1º using ACS and 5.9° using EYEDIAP datasets respectively. The proposed framework provides insight into the methodology of multi-feature fusion for gaze estimation.","PeriodicalId":308698,"journal":{"name":"2018 IEEE International Symposium on Multimedia (ISM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121100701","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

Extraction of Movie Trailer Biases Based on Editing Features for Trailer Generation 基于剪辑特征的电影预告片偏差提取

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.000-6

Honoka Kakimoto, Yuanyuan Wang, Yukiko Kawai, K. Sumiya

引用次数: 0

Neural Networks Based Fractional Pixel Motion Estimation for HEVC 基于神经网络的HEVC分数像素运动估计

2018 IEEE International Symposium on Multimedia (ISM) Pub Date : 2018-12-01 DOI: 10.1109/ISM.2018.00027

Ehab M. Ibrahim, Emad Badry, A. Abdelsalam, I. Abdalla, M. Sayed, Hossam Shalaby

引用次数: 8