Download or read book Using Classification for Analysis of Multi modal Video Summarization written by Brendan Wells and published by . This book was released on 2020 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Video Summarization refers to taking the important contents of a video and condensing it down to an easily consumable piece of data without having to watch the entire video. Currently, Millions of Videos are being recorded and shared every day. These videos range from the consumer level, such as a birthday party or wedding video, all the way up to industry such as film and television. We have constructed a model that seeks to address the problem of not being able to consume all the media that is being presented to you because of time constraints. To do this, we conduct two separate experiments. The first experiment examines the role of different parts of the summarization model, namely modality, sampling rate, and data scaling so that we better understand how summaries are generated. The second experiment utilizes these findings to create a model based in classification. We use classification as a means of interpreting a wide variety of types of video for summarization. By using classification to generate the video and audio features used by the summarizer, the classifier granularity is leveraged, and the maturity of classification problems is leveraged to accomplish a summarization task. We found that while scaling and sampling of the data have little effect on the overall summary, in each experiment the modality played a large role in the results. While many models exclude audio, we found that there are benefits to including this data when generating a video summary. We also found that the use of classification resulted in a separation of impacts for each modality, with video serving to construct the shape of the summary and audio determining importance score."--Abstract.

Download or read book Multimodal Video Characterization and Summarization written by Michael A. Smith and published by Springer Science & Business Media. This book was released on 2005-12-17 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Video Characterization and Summarization is a valuable research tool for both professionals and academicians working in the video field. This book describes the methodology for using multimodal audio, image, and text technology to characterize video content. This new and groundbreaking science has led to many advances in video understanding, such as the development of a video summary. Applications and methodology for creating video summaries are described, as well as user-studies for evaluation and testing.

Download or read book Video Content Analysis Using Multimodal Information written by Ying Li and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video Content Analysis Using Multimodal Information For Movie Content Extraction, Indexing and Representation is on content-based multimedia analysis, indexing, representation and applications with a focus on feature films. Presented are the state-of-art techniques in video content analysis domain, as well as many novel ideas and algorithms for movie content analysis based on the use of multimodal information. The authors employ multiple media cues such as audio, visual and face information to bridge the gap between low-level audiovisual features and high-level video semantics. Based on sophisticated audio and visual content processing such as video segmentation and audio classification, the original video is re-represented in the form of a set of semantic video scenes or events, where an event is further classified as a 2-speaker dialog, a multiple-speaker dialog, or a hybrid event. Moreover, desired speakers are simultaneously identified from the video stream based on either a supervised or an adaptive speaker identification scheme. All this information is then integrated together to build the video's ToC (table of content) as well as the index table. Finally, a video abstraction system, which can generate either a scene-based summary or an event-based skim, is presented by exploiting the knowledge of both video semantics and video production rules. This monograph will be of great interest to research scientists and graduate level students working in the area of content-based multimedia analysis, indexing, representation and applications as well s its related fields.

Download or read book Multimodal Learning toward Micro Video Understanding written by Liqiang Nie and published by Springer Nature. This book was released on 2022-05-31 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Micro-videos, a new form of user-generated contents, have been spreading widely across various social platforms, such as Vine, Kuaishou, and Tik Tok. Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to its brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for the high-order micro-video understanding. Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of the venue categories to guide the micro-video analysis; (3) how to alleviate the influence of low-quality caused by complex surrounding environments and the camera shake; (4) how to model the multimodal sequential data, {i.e.}, textual, acoustic, visual, and social modalities, to enhance the micro-video understanding; and (5) how to construct large-scale benchmark datasets for the analysis? These challenges have been largely unexplored to date. In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.

Download or read book Multimodal Processing and Interaction written by Petros Maragos and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents high quality, state-of-the-art research ideas and results from theoretic, algorithmic and application viewpoints. It contains contributions by leading experts in the obsequious scientific and technological field of multimedia. The book specifically focuses on interaction with multimedia content with special emphasis on multimodal interfaces for accessing multimedia information. The book is designed for a professional audience composed of practitioners and researchers in industry. It is also suitable for advanced-level students in computer science.

Download or read book Multi Modal Sentiment Analysis written by Hua Xu and published by Springer Nature. This book was released on 2023-11-26 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.

Download or read book Structured Video Content Analysis written by Yale Song and published by . This book was released on 2014 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video data exhibits a variety of structures: pixels exhibit spatial structure, e.g., the same class of objects share certain shapes and/or colors in image; sequences of frames exhibit temporal structure, e.g., dynamic events such as jumping and running have a certain chronological order of frame occurrence; and when combined with audio and text, there is multimodal structure, e.g., human behavioral data shows correlation between audio (speech) and visual information (gesture). Identifying, formulating, and learning these structured patterns is a fundamental task in video content analysis. This thesis tackles two challenging problems in video content analysis - human action recognition and behavior understanding - and presents novel algorithms to solve each: one algorithm performs sequence classification by learning spatio-temporal structure of human action; another performs data fusion by learning multimodal structure of human behavior. The first algorithm, hierarchical sequence summarization, is a probabilistic graphical model that learns spatio-temporal structure of human action in a fine-to-coarse manner. It constructs a hierarchical representation of video by iteratively summarizing the video sequence, and uses the representation to learn spatio-temporal structure of human action, classifying sequences into action categories. We developed an efficient learning method to train our model, and show that its complexity grows only sublinearly with the depth of the hierarchy. The second algorithm focuses on data fusion - the task of combining information from multiple modalities in an effective way. Our approach is motivated by the observation that human behavioral data is modality-wise sparse, i.e., information from just a few modalities contain most information needed at any given time. We perform data fusion using structured sparsity, representing a multimodal signal as a sparse combination of multimodal basis vectors embedded in a hierarchical tree structure, learned directly from the data. The key novelty is in a mixed-norm formulation of regularized matrix factorization via structured sparsity. We show the effectiveness of our algorithms on two real-world application scenarios: recognizing aircraft handling signals used by the US Navy, and predicting people's impression about the personality of public figures from their multimodal behavior. We describe the whole procedure of the recognition pipeline, from the signal acquisition to processing, to the interpretation of the processed signals using our algorithms. Experimental results show that our algorithms outperform state-of-the-art methods on human action recognition and behavior understanding.

Download or read book Structural Video Summarization Based on the Multimodal Semantic Analysis and Mining written by 陳伯煒 and published by . This book was released on 2009 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multimodal Analysis of User Generated Multimedia Content written by Rajiv Shah and published by Springer. This book was released on 2017-08-30 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a summary of the multimodal analysis of user-generated multimedia content (UGC). Several multimedia systems and their proposed frameworks are also discussed. First, improved tag recommendation and ranking systems for social media photos, leveraging both content and contextual information, are presented. Next, we discuss the challenges in determining semantics and sentics information from UGC to obtain multimedia summaries. Subsequently, we present a personalized music video generation system for outdoor user-generated videos. Finally, we discuss approaches for multimodal lecture video segmentation techniques. This book also explores the extension of these multimedia system with the use of heterogeneous continuous streams.

Download or read book Proceedings of the International Conference on Computational Intelligence and Sustainable Technologies written by Kedar Nath Das and published by Springer Nature. This book was released on 2022-02-12 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the collection of the accepted research papers presented in the 1st ‘International Conference on Computational Intelligence and Sustainable Technologies (ICoCIST-2021)’. This edited book contains the articles related to the themes on artificial intelligence in machine learning, big data analysis, soft computing techniques, pattern recognitions, sustainable infrastructural development, sustainable grid computing and innovative technology for societal development, renewable energy, and innovations in Internet of Things (IoT).

Download or read book Video Text Detection written by Tong Lu and published by Springer. This book was released on 2014-07-23 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems. Features: explains the fundamental theory in a succinct manner, supplemented with references for further reading; highlights practical techniques to help the reader understand and develop their own video text detection systems and applications; serves as an easy-to-navigate reference, presenting the material in self-contained chapters.

Download or read book 2019 6th International Conference on Signal Processing and Integrated Networks SPIN written by IEEE Staff and published by . This book was released on 2019-03-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference will be devoted to all advancements in Signal Processing and Integrated Networks Researchers from all over the country and abroad will gather in order to introduce their recent advances in the field and thereby promote the exchange of new ideas, results and techniques The conference will be a successive catalyst in promoting research work, sharing views and getting innovative ideas in this field

Download or read book Multimodal Biometric and Machine Learning Technologies written by Sandeep Kumar and published by John Wiley & Sons. This book was released on 2023-11-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners. Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication. This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties. Audience Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.

Download or read book Multimedia Database Retrieval written by Paisarn Muneesawang and published by Springer. This book was released on 2014-10-25 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, multimodal fusion, annotation, and database re-ranking. The application-oriented approach maximizes reader understanding of this complex field. Established researchers explain the latest developments in multimedia database technology and offer a glimpse of future technologies. The authors emphasize the crucial role of innovation, inspiring users to develop new applications in multimedia technologies such as mobile media, large scale image and video databases, news video and film, forensic image databases and gesture databases. With a strong focus on industrial applications along with an overview of research topics, Multimedia Database Retrieval: Technology and Applications is an indispensable guide for computer scientists, engineers and practitioners involved in the development and use of multimedia systems. It also serves as a secondary text or reference for advanced-level students interested in multimedia technologies.

Download or read book Research and Advanced Technology for Digital Libraries written by Mounia Lalmas and published by Springer Science & Business Media. This book was released on 2010-08-30 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 14th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2010, held in Glasgow, UK, in September 2010. The 22 long papers, 14 short papers, 19 posters and 9 demos presented in this volume were carefully reviewed and selected from 102 full paper submissions, 40 poster submissions, and 13 demo submissions. In addition the book contains the abstract of a keynote speech and an appendix stating information on the doctoral consortium, the workshops, and tutorials, as well as the panel, which were held at the conference. The papers are grouped in topical sections on system architectures, metadata, multimedia IR, interaction and interoperability, digital preservation, social Web/Web 2.0, search in digital libraries, (meta) analysis of digital libraries, query log analysis, cooperative work in DLs, ontologies, and domain-specific DLs, posters and demos.

Download or read book Multimedia Content Analysis written by Ajay Divakaran and published by Springer Science & Business Media. This book was released on 2009-03-02 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimedia Content Analysis: Theory and Applications covers the latest in multimedia content analysis and applications based on such analysis. As research has progressed, it has become clear that this field has to appeal to other disciplines such as psycho-physics, media production, etc. This book consists of invited chapters that cover the entire range of the field. Some of the topics covered include low-level audio-visual analysis based retrieval and indexing techniques, the TRECVID effort, video browsing interfaces, content creation and content analysis, and multimedia analysis-based applications, among others. The chapters are written by leading researchers in the multimedia field.

Download or read book Intelligent Systems and Applications written by Yaxin Bi and published by Springer Nature. This book was released on 2019-08-23 with total page 1312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends. This book collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.