2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)最新文献_第3页

Efficient automatic detection of 3D video artifacts 高效的3D视频伪影自动检测

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958787

Mohan Liu, Ioannis Mademlis, P. Ndjiki-Nya, Jean-Charles Le Quintrec, N. Nikolaidis, I. Pitas

引用次数: 3

Survey of web-based crowdsourcing frameworks for subjective quality assessment 主观质量评估的网络众包框架研究

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958831

T. Hossfeld, Matthias Hirth, Pavel Korshunov, Philippe Hanhart, B. Gardlo, Christian Keimel, C. Timmerer

引用次数: 43

Background subtraction under sudden illumination change 光照突然变化下的背景减法

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958814

Hasan Sajid, S. Cheung

引用次数: 13

Graph-based depth video denoising and event detection for sleep monitoring 基于图的深度视频去噪和睡眠监测事件检测

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958802

Cheng Yang, Yu Mao, Gene Cheung, V. Stanković, Kevin Chan

{"title":"Graph-based depth video denoising and event detection for sleep monitoring","authors":"Cheng Yang, Yu Mao, Gene Cheung, V. Stanković, Kevin Chan","doi":"10.1109/MMSP.2014.6958802","DOIUrl":"https://doi.org/10.1109/MMSP.2014.6958802","url":null,"abstract":"Quality of sleep greatly affects a person's physiological well-being. Traditional sleep monitoring systems are expensive in cost and intrusive enough that they disturb the natural sleep of clinical patients. In our previous work, we proposed a non-intrusive sleep monitoring system to first record depth video in real-time, then offline analyze recorded depth data to track a patient's chest and abdomen movements over time. Detection of abnormal breathing is then interpreted as episodes of apnoea or hypopnoea. Leveraging on recent advances in graph signal processing (GSP), in this paper we propose two new additions to further improve our sleep monitoring system. First, temporal denoising is performed using a block motion vector smoothness prior expressed in the graph-signal domain, so that unwanted temporal flickering can be removed. Second, a graph-based event classification scheme is proposed, so that detection of apnoea / hypopnoea can be performed accurately and robustly. Experimental results show first that graph-based temporal denoising scheme outperforms an implementation of temporal median filter in terms of flicker removal. Second, we show that our graph-based event classification scheme is noticeably more robust to errors in training data than two conventional implementations of support vector machine (SVM).","PeriodicalId":164858,"journal":{"name":"2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114179433","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: 18

Optimal detector for camera model identification based on an accurate model of DCT coefficients 基于精确DCT系数模型的相机模型识别优化检测器

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958810

T. H. Thai, R. Cogranne, F. Retraint

引用次数: 2

Music recommendation based on artist novelty and similarity 基于艺术家新颖性和相似性的音乐推荐

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958801

Ning Lin, Ping-Chia Tsai, Yu-An Chen, Homer H. Chen

引用次数: 10

Adaptive low complexity colour transform for video coding 用于视频编码的自适应低复杂度色彩变换

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958820

R. Weerakkody, M. Mrak

引用次数: 1

Performance evaluation of the emerging JPEG XT image compression standard 新兴的JPEG XT图像压缩标准的性能评估

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958834

A. Pinheiro, K. Fliegel, Pavel Korshunov, Lukáš Krasula, Marco V. Bernardo, Maria Pereira, T. Ebrahimi

{"title":"Performance evaluation of the emerging JPEG XT image compression standard","authors":"A. Pinheiro, K. Fliegel, Pavel Korshunov, Lukáš Krasula, Marco V. Bernardo, Maria Pereira, T. Ebrahimi","doi":"10.1109/MMSP.2014.6958834","DOIUrl":"https://doi.org/10.1109/MMSP.2014.6958834","url":null,"abstract":"The upcoming JPEG XT is under development for High Dynamic Range (HDR) image compression. This standard encodes a Low Dynamic Range (LDR) version of the HDR image generated by a Tone-Mapping Operator (TMO) using the conventional JPEG coding as a base layer and encodes the extra HDR information in a residual layer. This paper studies the performance of the three profiles of JPEG XT (referred to as profiles A, B and C) using a test set of six HDR images. Four TMO techniques were used for the base layer image generation to assess the influence of the TMOs on the performance of JPEG XT profiles. Then, the HDR images were coded with different quality levels for the base layer and for the residual layer. The performance of each profile was evaluated using Signal to Noise Ratio (SNR), Feature SIMilarity Index (FSIM), Root Mean Square Error (RMSE), and CIEDE2000 color difference objective metrics. The evaluation results demonstrate that profiles A and B lead to similar saturation of quality at the higher bit rates, while profile C exhibits no saturation. Profiles B and C appear to be more dependent on TMOs used for the base layer compared to profile A.","PeriodicalId":164858,"journal":{"name":"2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115435588","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

Automatic high dynamic range hallucination in inverse tone mapping 自动高动态范围幻觉在反色调映射

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958828

Pin-Hung Kuo, Huai-Jen Liang, Chi-Sun Tang, Shao-Yi Chien

{"title":"Automatic high dynamic range hallucination in inverse tone mapping","authors":"Pin-Hung Kuo, Huai-Jen Liang, Chi-Sun Tang, Shao-Yi Chien","doi":"10.1109/MMSP.2014.6958828","DOIUrl":"https://doi.org/10.1109/MMSP.2014.6958828","url":null,"abstract":"Nowadays the dynamic range of displays has been higher and higher, which means that contents can be recorded and displayed with more detail. However, the original low dynamic range contents were recorded in a lower dynamic range. Such contents will be unsatisfying compared to high dynamic range contents, especially in the saturated, or overexposed region. This paper proposes an algorithm to compensate such exposed regions, which is called automatic high dynamic range image hallucination for inverse tone mapping. Inverse tone-mapping is the process of creating a high dynamic range image from a single low dynamic range image. In this work, high dynamic range image hallucination is used as the key method to reproduce the information which is lost in the low dynamic range image capturing. Previous methods require user interaction as a hallucination criteria, and is not practical in some applications where user interaction is not available. In this paper, the hallucination is performed automatically with the assistance of luminance and texture decoupling process. This scheme produces visually satisfying results and has the potential to be applied to video inverse tone-mapping with its automatic property.","PeriodicalId":164858,"journal":{"name":"2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106714","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: 3

View-invariant feature discovering for multi-camera human action recognition 多相机人体动作识别的视点不变特征发现

2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP) Pub Date : 2014-11-20 DOI: 10.1109/MMSP.2014.6958807

Hong Lin, L. Chaisorn, Yongkang Wong, Anan Liu, Yuting Su, M. Kankanhalli

{"title":"View-invariant feature discovering for multi-camera human action recognition","authors":"Hong Lin, L. Chaisorn, Yongkang Wong, Anan Liu, Yuting Su, M. Kankanhalli","doi":"10.1109/MMSP.2014.6958807","DOIUrl":"https://doi.org/10.1109/MMSP.2014.6958807","url":null,"abstract":"Intelligent video surveillance system is built to automatically detect events of interest, especially on object tracking and behavior understanding. In this paper, we focus on the task of human action recognition under surveillance environment, specifically in a multi-camera monitoring scene. Despite many approaches have achieved success in recognizing human action from video sequences, they are designed for single view and generally not robust against viewpoint invariant. Human action recognition across different views remains challenging due to the large variations from one view to another. We present a framework to solve the problem of transferring action models learned in one view (source view) to another view (target view). First, local space-time interest point feature and global shape-flow feature are extracted as low-level feature, followed by building the hybrid Bag-of-Words model for each action sequence. The data distribution of relevant actions from source view and target view are linked via a cross-view discriminative dictionary learning method. Through the view-adaptive dictionary pair learned by the method, the data from source and target view can be respectively mapped into a common space which is view-invariant. Furthermore, We extend our framework to transfer action models from multiple views to one view when there are multiple source views available. Experiments on the IXMAS human action dataset, which contains videos captured with five viewpoints, show the efficacy of our framework.","PeriodicalId":164858,"journal":{"name":"2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)","volume":"17 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122375682","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