Guest editorial special issue on intelligent multimedia processing
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H UMAN communication is intrinsically multimodal. With the advances of technology, modern communication systems will also become more and more multimodal. Hence, mul-timedia technologies represent new ground for research interactions among a variety of media such as speech, audio, image, video, text, and graphics. Future multimedia technologies will need to handle information with an increasing level of intelligence , i.e., automatic recognition and interpretation of mul-timodal signals. This is particularly emphasized in MPEG-7 which focuses on the " multimedia content description interface. " The description shall be associated with the content itself to facilitate fast and effective searching for all the media. Specifically , the MPEG-7 research domain will cover techniques for content-based indexing and retrieval: pattern recognition, face detection/recognition, and fusion of multimodality. Intelligent multimedia processing shares three fundamental goals with biological systems: 1) universal data processing engine for multimodal signals; 2) multimodality; and 3) unsu-pervised clustering and/or supervised learning by examples. Because of these features, neural networks are attractive candidates for intelligent multimedia processing and recent activity in the area is a proof of this fact. The main attribute of neural computing is its adaptive learning capability, which enables interpretations of possible variations of a same object or pattern, e.g., with respect to scale, orientation, and perspective. Moreover, they are able to accurately approximate unknown systems based on sparse sets of noisy data. Certain neural models also effectively incorporate statistical signal processing and optimization techniques. In addition, spatial/temporal neural structures and hierarchical models are promising for multirate, multiresolution multimedia processing. As a result, many successful applications of neural networks in intelligent multimedia processing, sometimes combined with fuzzy systems and evolutionary computing, have been reported. This special issue serves as a forum for recent development in intelligent multimedia processing. The 20 papers published in this special issue cover a wide range of computational intelligence techniques and applications in various multimedia processing tasks. Five papers in the issue explore intelligent techniques in media indexing and retrieval. The invited paper by Naphade and Huang reviews state-of-the-art techniques in multimedia retrieval techniques. They discussed how multimedia retrieval can be viewed as a pattern recognition problem, and how reliance on powerful pattern recognition and machine learning techniques is increasing in the field of multimedia retrieval. They also discuss how semantic retrieval Publisher Item Identifier S 1045-9227(02)06364-6. is centered around concepts and context, and also discuss various mechanisms for modeling concepts and context. Guo …