Sethuraman Panchanathan

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The estimation of head pose angle from face images is an integral component of face recognition systems, human computer interfaces and other human-centered computing applications. To determine the head pose, face images with varying pose angles can be considered to be lying on a smooth low-dimensional manifold in high-dimensional feature space. While(More)
This paper presents a VLSI implementation of discrete wavelet transform (DWT). The architecture is simple, modular, and cascadable for computation of one, or multi-dimensional DWT. It comprises of four basic units: input delay, filter, register bank, and control unit. The proposed architecture is systolic in nature and performs both high-pass and low-pass(More)
Real-time transmission of video data in network environments, such as wireless and Internet, is a challenging task, as it requires high compression efficiency and network friendly design. H.264/AVC is the newest international video coding standard, jointly developed by groups from ISO/IEC and ITU-T, which aims at achieving improved compression performance(More)
In this paper, we present a methodology for precisely comparing the robustness of face recognition algorithms with respect to changes in pose angle and illumination angle. For this study, we have chosen four widely-used algorithms: two subspace analysis methods (principle component analysis (PCA) and linear discriminant analysis (LDA)) and two probabilistic(More)
We consider the characterization of muscle fatigue through a noninvasive sensing mechanism such as Surface ElectroMyoGraphy (SEMG). While changes in the properties of SEMG signals with respect to muscle fatigue have been reported in the literature, the large variation in these signals across different individuals makes the task of modeling and(More)
-Histogram comparison is a popular technique for image and video indexing. The complexity of the technique can be reduced by representing the histogram by its moments. In this paper, we propose two techniques to improve the performance of basic histogram/moment-based technique. First, we propose to use orthogonal Legendre moments for representing(More)
Active Learning is a machine learning and data mining technique that selects the most informative samples for labeling and uses them as training data; it is especially useful when there are large amount of unlabeled data and labeling them is expensive. Recently, batch-mode active learning, where a set of samples are selected concurrently for labeling, based(More)
Discriminative learning when training and test data belong to different distributions is a challenging and complex task. Often times we have very few or no labeled data from the test or target distribution but may have plenty of labeled data from multiple related sources with different distributions. The difference in distributions may be both in marginal(More)
SUMMARY Images containing spatial expression patterns illuminate the roles of different genes during embryogenesis. In order to generate initial clues to regulatory interactions, biologists frequently need to know the set of genes expressed at the same time at specific locations in a developing embryo, as well as related research publications. However,(More)