Verhaegh W., Aarts E., Korst J. Algorithms in Ambient Intelligence

Springer, 2004. — 347 p.The advent of the digital era, the Internet, and the development of fast computing devices that can access mass storage servers at high communication bandwidths have brought within our reach the world of ambient intelligent systems. These systems provide users with information, communication, and entertainment at any desired place and time. Since its introduction in 1998, the vision of Ambient Intelligence has attracted much attention within the research community. Especially, the need for intelligence generated by smart algorithms, which run on digital platforms that are integrated into consumer electronics devices, has strengthened the interest in Computational Intelligence. This newly developing research field, which can be positioned at the intersection of computer science, discrete mathematics, and artificial intelligence, contains a large variety of interesting topics including machine learning, content management, vision, speech, data mining, content augmentation, profiling, contextual awareness, feature extraction, resource management, security, and privacy.
Over the past years major progress has been made in the development and analysis of intelligent algorithms for ambient intelligent systems. This has led to the build-up of a new community of practice within Philips Research, and hence we organized the Symposium on Intelligent Algorithms (SOIA) to provide all those who are actively involved in the design and analysis of intelligent algorithms within Philips with the opportunity to gather and exchange information about the progress achieved in this new field of research. As we considered the presented material to be of interest to a much larger audience, we invited the authors to submit their papers to this book.Algorithms in Ambient Intelligence
Part I User Interaction
Multimodality and Ambient Intelligence
From Stereotypes to Personal Profiles via Viewer Feedback
CubyHum: Algorithm for Query by Humming
Personalized Multimedia Summarization
Features for Audio Classification
Information Retrieval in the Audio Domain
Approaches in Machine Learning
Machine Learning for Ambient Intelligence: Boosting in Automatic Speech Recognition
Exchange Clustering and EM Algorithm for Phrase Classification in Telephony Applications
Part II System Interaction
Algorithms for Audio and Video Fingerprinting
Near Video-on-Demand with Limited Client Bandwidth and Distributed Servers
Methods to Optimally Trade Bandwidth against Buffer Size for a VBR Stream
Dynamic Control of Scalable Media Processing Applications
Saving Energy in Portable Multimedia Storage
Storage of VBR Video Content on a Multi-Zone Recording Disk based on Resource Usage
Test Resource Management and Scheduling for Modular Manufacturing Test of SOCs