Automated classification of phonological errors in aphasic language

Using heuristically guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work is significant because it introduces and evaluates a novel approach to error simulation and classification, provides a prototype simulation tool for neurolinguistic research, and forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.     

Matching two perspective views

A computational approach to image matching is described. It uses multiple attributes associated with each image point to yield a generally overdetermined system of constraints, taking into account possible structural discontinuities and occlusions. In the algorithm implemented, intensity, edgeness, and cornerness attributes are used in conjunction with the constraints arising from intraregional smoothness, field continuity and discontinuity, and occlusions to compute dense displacement fields and occlusion maps along the pixel grids. The intensity, edgeness, and cornerness are invariant under rigid motion in the image plane. In order to cope with large disparities, a multiresolution multigrid structure is employed. Coarser level edgeness and cornerness measures are obtained by blurring the finer level measures. The algorithm has been tested on real-world scenes with depth discontinuities and occlusions. A special case of two-view matching is stereo matching, where the motion between two images is known. The algorithm can be easily specialized to perform stereo matching using the epipolar constraint     

Superresolution and noise filtering using moving least squares.

An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied.     

Performance analysis of stereo, vergence, and focus as depth cuesfor active vision

This paper compares the performances of the binocular cues of stereo and vergence, and the monocular cue of focus for range estimation using an active vision system. The performance of each cue is characterized in terms of sensitivity to errors in the imaging parameters. The effects of random, quantization errors are expressed in terms of the standard deviation of the resulting depth error. The effect of systematic, calibration errors on estimation using each cue is also studied. Performance characterization of each cue is utilized to evaluate the relative performance of the cues. Also discussed, based on such characterization, are ways to select a cue taking into account the computational and reliability aspects of the corresponding estimation process     

Alprazolam in chronic tension type headache

Alprazolam was evaluated in the treatment of 62 patients of chronic tension type headache using a double blind cross over design with random allocation to drug or placebo. The duration of the trial was 4 months with a 2 week run in period and 2 week washout period separating two treatment periods of 4 weeks each. The patients were followed up for 4 weeks at the completion of the trial. 48 patients completed the trial. There was no significant difference in the overall response rate based in terms of percentage reduction in headache frequency per week, however a significant decrease in headache index was observed during treatment with alprazolam as compared to placebo (P < 0.05). The mean analgesic intake per week was also significantly lower during treatment with alprazolam as compared to the run in period. Side effects were seen in 16.67% patients. In none of the patients was it significant enough to require withdrawal from the study.     

Integrated Matching and Segmentation of Multiple Features in Two Views

We present an integrated method to match multiple features including points, regions, and lines in two perspective images, and simultaneously segment them such that all features in each segment have the same 3D motion. The method uses local affine (first-order) approximation of the displacement field under the assumption of locally rigid motion. Each distinct motion is represented in the image plane by a distinct set of values for six displacement parameters. To compute the values of these parameters, the 6D space is split into two 3D spaces, and each is exhaustively searched coarse-to-fine. This yields two results simultaneously, correspondences between features and segmentation of features into subsets corresponding to locally rigid patches of moving objects. Since matching is based on the 2D approximation of 3D motion, problems due to motion or object boundaries and occlusion can be avoided. Large motion is also handled in a manner unlike the methods based on flow field. Integrated use of the multiple features not only gives a larger number of features (overconstrained system) but also reduces the number of candidate matches for the features, thus making matching less ambiguous. Experimental results are presented for four pairs of real images.     

MOFA: a model for fault and availability in complex services

Asset allocation to optimize reliability and availability (R&A) has been studied in the literature. However, these concepts have not been investigated in combination with degraded performance in realistic reliability-models. Some reliability models, techniques, and tools allow modeling of degradable performance. However, they are mainly used in evaluating R&A of given systems; they do not consider the inverse problem of determining the system parameters that would maximize the R&A. This paper provides a realistic reliability model for complex services; the model can be used to study the asset allocation problem in degradable complex services. This paper uses a simple model to describe the failure characteristics of the system parts. This model provides: (1) an infrastructure for defining R&A in a flexible way, and (2) a way of defining at what level of availability it is worth offering the service, and at what level of failure of resources the system should be declared faulty. This model is then used to `allocate optimally the available assets' to `implement a service that is tailored to the availability needs of the user and the situation'. The model is applied to a realistic example of a complex service, viz. a multimedia communication service     

Detecting faces in images: a survey

Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research