Información del Diario
Multimedia Tools and Applications
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Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools, and case studies of multimedia applications. Experimental and survey articles are appropriate for the journal. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed.

Specific areas of interest include (but are not limited to):

Multimedia Tools:
Multimedia application enabling software
System software support for multimedia
Performance measurement tools for multimedia
Multimedia authoring tools
System hardware support for multimedia
Multimedia databases and retrieval
Web tools and applications
Multimedia Applications:
Prototype multimedia systems and platforms
Multimedia on information superhighways

Video on-demand
Interactive TV
Home shopping
Remote home care
Electronic album
Personalized electronic journals
Última Actualización Por Dou Sun en 2017-09-15
Special Issues
Special Issue on Large-Scale Heterogeneous Multimedia Data Computing and Understanding
Día de Entrega: 2017-09-27

We are living in the era of large-scale multimedia data in a heterogeneous space. This era not only provides new opportunities to jointly represent objects from distinct aspects, but also brings great challenges in data understanding and analysis. Apart from the traditional audios, images, and videos, data in this era exhibit unprecedented modalities, such as user connections, user behaviors, and geographical annotations. To gain insightful understanding and analysis into the data, recent years have witnessed the wave of a variety of machine learning algorithms and frameworks, ranging from deep learning to quantum learning models. It therefore becomes vital to report the very recent progress in advanced machine learning methodologies and state-of-the-arts for handling large-scale heterogeneous multimedia data. We are targeting at inviting original research outputs in this field, including new theories, applications, benchmark datasets, and new industrial deployments on the topic. The list of possible topics includes, but not limited to: 1. Large-scale heterogeneous media data computing - Multimodal media data acquisition - Image/video feature extraction - Heterogeneous data feature learning - Deep learning methods for media computing 2. Large-scale heterogeneous media data management - Multimodal data indexing - Hash methods with multimodal data - Search with multimodal data - Cross-view or cross-modal Search 3. Large-scale heterogeneous media understanding - Retrieval, classification and recognition with multimodal data - Multi-View or Multimodal data fusion technique - Multimodal dictionary learning technique - Human-Computer-Interaction with multimodal data - Learning methods using multimodal data - Deep learning methods for heterogeneous feature fusion
Última Actualización Por Dou Sun en 2017-06-03
Special Issue on Content Based Multimedia Indexing
Día de Entrega: 2017-10-15

Multimedia indexing systems aim at providing user-friendly, fast and accurate access to large multimedia repositories. Various tools and techniques from different fields such as data indexing, machine learning, pattern recognition, and human computer interaction have contributed to the success of multimedia systems. In spite of significant progress in the field, content-based multimedia indexing systems still show limits in accuracy, generality and scalability. The goal of this special issue is to bring forward recent advancements in content-based multimedia indexing. In addition to multimedia and social media search and retrieval, we wish to highlight related and equally important issues that build on content-based indexing, such as multimedia content management, user interaction and visualization, media analytics, etc. The special issue will also feature contributions on application domains, e.g., deep learning for multimedia indexing, sparse data learning, cultural heritage and synergetic media production.
Última Actualización Por Dou Sun en 2017-04-13
Special Issue on Next Applications in Multimedia Computing
Día de Entrega: 2017-11-30

We are surrounded by a vast amount of multimedia contents, which are generated by various sources, from both professionals and amateurs, and many people consume multimedia content everyday. Despite the vast amount of documents describing all types of multimedia technologies, it is about time to have a new prospective to foresee how new techniques from various areas interact with multimedia techniques or applications. For example, mobile cloud computing is a new research topic. It is nature to ask what kind of multimedia applications such a technique could apply and what potential difficulties are to be solved. As a second example, traditional virtual reality glasses are expensive, and now we have a cheap alternative (Google cardboard VR kit) with the aid of a smartphone. To this end, we may wander if we can produce immersive audio by using a smartphone. As a third example, convolutional neural network is shown to outperform traditional methods in image recognition problems. If such a technique is applied to retrieval and indexing of general multimedia contents, can better performance be achieved? We need more evidences to answer these questions. Furthermore, if multimedia content is to be consumed in a living room, the current trend is to have ultra high picture resolution (4 K and above) rendered with spatially layered audio (such as 22.2 channels arranged as top, middle, and bottom layers). To successfully deploy this type of multimedia content, we need new production machines, compression techniques, transmission media and methods, and new rendering devices and layout studies. Certainly, motion pictures with ultra high resolution can have many more applications yet to be studied. This special issue is soliciting high quality technical papers addressing research achievements, practices and challenges for emergent multimedia techniques. Original and research articles are solicited in all aspects of including theoretical studies, practical applications, new social technology and experimental prototypes. This special issue calls for original papers describing the latest developments, trends, and solutions of the promotion of multimedia techniques. Topics of interests include, but are not limited to: - Immersive audio - Multimedia indexing and retrieval - Augmented/Virtual reality - New image/audio/video compression techniques - Data mining, analysis and re-production for multimedia computing - New methods on privacy and security in multimedia - New techniques on information communication and networking in multimedia - Embedded system for multimedia applications - UI/UX for multimedia contents - Tools for multimedia content generations - Verification and testing for multimedia software
Última Actualización Por Dou Sun en 2017-09-15
Special Issue on Spatial-Temporal Feature Learning for Unconstrained Video Analysis
Día de Entrega: 2017-12-15

With the development of mobile Internet and personal devices, we are witnessing an explosive growth of video data on the Web. This has encouraged the research of video analysis. Compared to the trimmed videos in the open benchmark datasets, most of the real-world videos are unconstrained. Firstly, as captured under different conditions, unconstrained videos usually have large intra-class differences. Secondly, as captured by different devices and people, unconstrained videos may own more variants in quality. The success of hand-crafted descriptors lies in the simultaneously incorporating spatial description of each frame and temporal consistency of successive frames. Recently, researchers have tried to learn video representations from deep ConvNets, where the promising progresses were obtained owing to the breakthrough in the appropriately pooling or encoding of temporal information of video sequences in the deep neural networks. As the visual content and temporal consistency of unconstrained videos are more complex, there are still challenges in video analysis and practical applications. This special issue serves as a forum for researchers all over the world to discuss their works and recent advances in video feature learning and its applications in real world applications. Both state-of-the-art works, as well as benchmark datasets and literature reviews, are welcome for submission. This special issue seeks to present and highlight the latest developments on practical methods of unconstrained video analysis. Papers addressing interesting real-world applications are especially encouraged. Topics of interest include, but are not limited to, - Feature learning by multi-cue fusion for unconstrained video analysis - Pooling the spatial-temporal layers in deep ConvNets - End-to-end integration of RNN and CNN for video feature learning - Effective feature learning for video captioning - Ad hoc feature learning for video event detection - Adapt un-labeled videos for robust feature learning - Transfer feature learning for video analysis - Spatial-temporal hashing and indexing for large-scale video retrieval - Unconstrained video benchmark for the evaluation of future learning - Real-world applications of unconstrained video analysis with future learning, e.g., event detection, action recognition, retrieval, summarization, synthesis, and video-to-language captioning.
Última Actualización Por Dou Sun en 2017-06-14
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