A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Interview with Paul DeMarinis

Since the early 1970s, the American electronic media artist Paul DeMarinis (b. 1948, Cleveland, Ohio, USA) has created works that re-imagine modes of communication and reinvent the technologies that enable communication. His works (see Table 1) have taken shape as recordings, performances, electronic inventions, and site-specific and interactive installations; many are considered landmarks in the histories of electronic music and media art. Paul DeMarinis pioneered live performance with computers, collaborated on landmark works with artists like David Tudor and Robert Ashley, undertook several tours with the Merce Cunningham Dance Company, and brought to life obscure technologies such as the flame loudspeaker (featured in his 2004 sculpture Firebirds). His interactive installation The Music Room (1982), commissioned by Frank Oppenheimer for the Exploratorium in San Francisco, was the first automatic music work to reach a significant audience. His album Music As A Second Language (1991) marks one of the most extensive explorations of the synthesized voice and speech melodies to date. Installations like The Edison Effect (1989-1993), in which lasers scan ancient recordings to produce music, and The Messenger (1998/2005), in which electronic mail messages are displayed on alphabetic telegraph receivers, illustrate a creative process that Douglas Kahn (1994) has called "reinventing invention." [etc]

Dartmouth Symposium on the Future of Computer Music Software: A Panel Discussion

Transcript of a Panel Discussion at the Dartmouth Symposium, chaired by Eric Lyon.

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.