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Pressestimmen
From the reviews: "A book that focuses on the intersection and intersection of these two fast-growing areas could not be better timed. … the book is organized into three major parts that cover audio and video processing, machine learning, and applications. … On the whole, this is a valuable and timely reference book for those interested in machine learning or audio, video, and image processing, although the need for a well-integrated book on this topic still remains." (M. Sasikumar, ACM Computing Reviews, December, 2008) "…this book, unlike most other books in this field, not only introduces a few widely used techniques in audio and image analysis, but also discusses the latest advancements in the field. …Distinct from other books, it also points out several public software packages and benchmark data sets that encourage the reader to have a hands-on experience on how machine-learning techniques work to analyze audio and visual content. Its comprehensive coverage on recent development in this research area makes it easy for experienced researchers to further explore the latest techniques. …it is ideal as a textbook or supplemental material for senior graduate courses or advanced topic seminars." (Jie Yu, Journal of Electronic Imaging, Vol. 18, Apr–Jun 2009)
Kurzbeschreibung
Focusing on complex media and how to convert raw data into useful information, this book offers both introductory and advanced material in the combined fields of machine learning and image/video processing. It is organized into three parts. The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing. The third focuses on applications and shows how techniques are applied in actual problems. Examples and problems are based on data and software packages publicly available on the web.
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis
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2 von 2 Kunden fanden die folgende Rezension hilfreich
A pretty good effort for a complex topic
7. März 2008
Format:Gebundene Ausgabe
This book is divided into three parts:
From Perception to Computation - Shows how the physical supports our auditory and visual perceptions. In other words, it shows how acoustic waves and electromagnetic radiation are converted into objects that can be manipulated by a computer.
Machine Learning - Provides a rather deep survey of the main techniques used in machine learning. These chapters cover most of the algorithms applied in systems for audio, image, and video analysis. At this point, all of the algorithms are general pattern recognition techniques that could apply to any field.
Applications - This section presents examples of applications using the techniques presented in part two. There is a chapter each dedicated to speech and handwriting recognition, face recognition, and video segmentation and keyframe extraction. Each chapter shows an overall system where analysis and machine learning components interact in order to accomplish a given task. Whenever possible the chapters of this part present results obtained using publicly available data and software package. This enables the reader to perform experiments similar to those presented in this book.
The beginning of each chapter starts with what the reader should understand before getting started, such as calculus and chapter four in the case of chapter eleven. That is followed with a list of what the reaer should know after reading the chapter. I'd say parts one and two are quite good, but things break down a bit in part three. Granted, the subject of each of the three chapters in the final section is complex, but a few more figures and labeled algorithmic steps and maybe a little less prose might have made the specific matters of each task at hand clearer.
From Perception to Computation - Shows how the physical supports our auditory and visual perceptions. In other words, it shows how acoustic waves and electromagnetic radiation are converted into objects that can be manipulated by a computer.
Machine Learning - Provides a rather deep survey of the main techniques used in machine learning. These chapters cover most of the algorithms applied in systems for audio, image, and video analysis. At this point, all of the algorithms are general pattern recognition techniques that could apply to any field.
Applications - This section presents examples of applications using the techniques presented in part two. There is a chapter each dedicated to speech and handwriting recognition, face recognition, and video segmentation and keyframe extraction. Each chapter shows an overall system where analysis and machine learning components interact in order to accomplish a given task. Whenever possible the chapters of this part present results obtained using publicly available data and software package. This enables the reader to perform experiments similar to those presented in this book.
The beginning of each chapter starts with what the reader should understand before getting started, such as calculus and chapter four in the case of chapter eleven. That is followed with a list of what the reaer should know after reading the chapter. I'd say parts one and two are quite good, but things break down a bit in part three. Granted, the subject of each of the three chapters in the final section is complex, but a few more figures and labeled algorithmic steps and maybe a little less prose might have made the specific matters of each task at hand clearer.
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