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Multimodal information processing has received considerable attention in recent years. The focus of existing research in this area has been predominantly on the use of fusion technology. In this paper, we suggest that cross-modal association can provide a new set of powerful solutions in this area. We investigate different cross-modal association methods(More)
Talking face detection is important for videoconferencing. However, the detection of the talking face is difficult because of the low resolution of the capturing devices, the informal style of communication and the background sounds. In this paper, we present a novel method for finding the talking face using latent semantic indexing approach. We tested our(More)
This paper proposes a new active learning approach, confidence-based active learning, for training a wide range of classifiers. This approach is based on identifying and annotating uncertain samples. The uncertainty value of each sample is measured by its conditional error. The approach takes advantage of current classifiers' probability preserving and(More)
This paper discusses the use of a combination of support vector machine and decision tree learning for recognizing four emotions in speech, which are Neutral, Angry, Lombard, and Loud. The base features selected were pitch, derivative of pitch, energy, speaking rate, formants, band-widths, and Mel Frequency Cepstral Coefficients. Three methods of combining(More)
In this paper we present a region growing approach for color images using an online learning algorithm that aims for content-based image retrieval systems. Our learning algorithm follows a variation of Bayesian estimation procedure to characterize each region as it is grown. The resulting image growing procedure is simple to implement , robust to initial(More)