INFORMATION RETRIEVAL FOR MUSIC AND MOTION PDF
Music Information Retrieval. 1. Outline of Part I. 3. Further Notes. 4. Motion Retrieval. 5. Outline of Part II. 7. Further Notes. 9. Alberto Pinto, Goffredo Haus, A Framework for Music Content Description and Retrieval, Proceedings of the 12th European conference on Research and. Information Retrieval for Music and Motion. Bearbeitet von. Meinard Müller. 1. Auflage Buch. xvi, S. Hardcover. ISBN 3 6. Format (B x .
|Language:||English, Spanish, Japanese|
|Genre:||Fiction & Literature|
|ePub File Size:||21.60 MB|
|PDF File Size:||20.14 MB|
|Distribution:||Free* [*Regsitration Required]|
PDF | The second part of this monograph deals with content-based analysis and retrieval of 3D motion capture data as used in computer graphics for animating. Information Retrieval for Music and Motion ISBN ; Digitally watermarked, DRM-free; Included format: PDF; ebooks can be used on all. Lecture. Information Retrieval for Music and Motion. Meinard Müller. Max-Planck- Institut für Informatik. Campus E1 4, Saarbrücken, Germany.
Content-based multimedia retrieval is a challenging research field with many unsolved problems. This monograph details concepts and algorithms for robust and efficient information retrieval of two different types of multimedia data: It first examines several approaches in music information retrieval, in particular general strategies as well as efficient algorithms. The book then introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization. The challenge is to organize, understand, and search multimodal information in a robust, efficient and intelligent manner. The present monograph significantly advances the state of the art and introduces novel concepts and algorithms for content-based analysis and retrieval for music data Part I and motion data Part II.
Write a customer review. Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers. Learn more about Amazon Giveaway. This item: Information Retrieval for Music and Motion. Set up a giveaway.
Customers who bought related items also bought. Music Data Analysis: Signal Processing Methods for Music Transcription.
Ian Goodfellow. The Elements of Statistical Learning: Artificial Intelligence: A Modern Approach. Deep Learning with Python. Francois Chollet. There's a problem loading this menu right now.
Learn more about Amazon Prime.
Information Retrieval for Music and Motion
Get fast, free shipping with Amazon Prime. Back to top. Get to Know Us.
Amazon Payment Products. English Choose a language for shopping. Amazon Music Stream millions of songs. Amazon Advertising Find, attract, and engage customers.
Amazon Drive Cloud storage from Amazon. Alexa Actionable Analytics for the Web. AmazonGlobal Ship Orders Internationally.
Amazon Inspire Digital Educational Resources.
Amazon Rapids Fun stories for kids on the go. Amazon Restaurants Food delivery from local restaurants. ComiXology Thousands of Digital Comics. DPReview Digital Photography. East Dane Designer Men's Fashion. Shopbop Designer Fashion Brands. Deals and Shenanigans. PillPack Pharmacy Simplified. This makes content-based multimedia retrieval a challenging research field with many unsolved problems.
In Part I, he discusses in depth several approaches in music information retrieval, in particular general strategies as well as efficient algorithms for music synchronization, audio matching, and audio structure analysis. He also shows how the analysis results can be used in an advanced audio player to facilitate additional retrieval and browsing functionality. In Part II, he introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization.
The detailed chapters at the beginning of each part give consideration to the interdisciplinary character of this field, covering information science, digital signal processing, audio engineering, musicology, and computer graphics.
This first monograph specializing in music and motion retrieval appeals to a wide audience, from students at the graduate level and lecturers to scientists working in the above mentioned fields in academia or industry. Lecturers and students will benefit from the didactic style, and each unit is suitable for stand-alone use in specialized graduate courses. Researchers will be interested in the detailed description of original research results and their application in real-world browsing and retrieval scenarios.
Information Retrieval for Music and Motion | Meinard Müller | Springer
His research interests include digital signal processing, multimedia information retrieval, computational group theory, and combinatorics. His special research topics include audio signal processing, computational musicology, analysis of 3D motion capture data, and content-based retrieval in multimedia documents. The challenge is to organize, understand, and search multimodal information in a robust, efficient and intelligent manner.
The present monograph significantly advances the state of the art and introduces novel concepts and algorithms for content-based analysis and retrieval for music data Part I and motion data Part II. Each part is suitable for use as stand-alone lecture notes for a graduate course in Computer Science. The monograph skillfully highlights the interaction between modeling, experimentation, and mathematical theory while introducing the students to current research fields.
It introduces many new results in two upcoming areas within multimedia retrieval: In both parts of the book, efficiency and robustness are key issues, and indeed vital motivations in multimedia retrieval.
The author has clearly established himself at the frontier of the the research field in multimedia retrieval. Overall, this volume is a good introduction into and survey of current research in the area of multimedia retrieval.
The Bonn mathematics group from which it issues enjoys its own special distinction in the development of rigorous applications with wide applicability. This collection of state-of-the-art techniques is an essential reference for researchers in computer graphics, computer vision, computer music, and multimedia.
- SPARKS RISE ALEXANDRA BRACKEN EPUB
- THE BURNING LAND EBOOK
- BEST BOOK FOR PHP PDF
- AIRTEL PREPAID FORM PDF
- UNDERSTANDING NUTRITION 13TH EDITION EBOOK
- GET HIM BACK FOREVER EBOOK
- COMPUTER NETWORKS FOROUZAN 2ND EDITION PDF
- CRYPTOGRAPHY NETWORK SECURITY BEHROUZ FOROUZAN EBOOK
- NUMERIA LAND OF FALLEN STARS PDF
- LEAN PRODUCTION SIMPLIFIED BY PASCAL DENNIS PDF
- WEB TECHNOLOGY BY PANKAJ SHARMA PDF
- STARTING WITH STRUTS2 PDF
- PROGRAMMING .NET WEB SERVICES BOOK