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Prediction of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of major interest in AD research. A large number of potential predictors have been proposed, with most investigations tending to examine one or a set of related predictors. In this study, we simultaneously examined multiple features from different modalities of(More)
We present a method to automatically outline the optic disc in a retinal image. Our method for finding the optic disc is based on the properties of the optic disc using simple image processing algorithms which include thresholding, detection of object roundness and circle detection by Hough transformation. Our method is able to recognize the retinal images(More)
—The extensive amount of multimedia information available necessitates content-based video indexing and retrieval methods. Since humans tend to use high-level semantic concepts when querying and browsing multimedia databases, there is an increasing need for semantic video indexing and analysis. For this purpose, we present a unified framework for semantic(More)
Emotional factors directly reflect audiences' attention, evaluation and memory. Affective contents analysis not only create an index for users to access their interested movie segments, but also provide feasible entry for video highlights. Most of the work focus on emotion type detection. Besides emotion type, emotion intensity is also a significant clue(More)
Emotional factors directly reflect audiences’ attention, evaluation and memory. Recently, video affective content analysis attracts more and more research efforts. Most of the existing methods map low-level affective features directly to emotions by applying machine learning. Compared to human perception process, there is actually a gap between low-level(More)
The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking that is intended as a step towards head and face tracking for a perceptual user interface. In this paper, we review the CamShift Algorithm and extend a default implementation to allow tracking in an arbitrary number and type of feature(More)
TV advertising is ubiquitous, perseverant, and economically vital. Millions of people's living and working habits are affected by TV commercials. In this paper, we present a multimodal ("visual + audio + text") commercial video digest scheme to segment individual commercials and carry out semantic content analysis within a detected commercial segment from(More)
We study the problem of affective content analysis. In this paper we think of affective contents as those video/audio segments, which may cause an audience's strong reactions or special emotional experiences, such as laughing or fear. Those emotional factors are related to the users' attention, evaluation, and memories of the content. The modeling of(More)
In this paper, we describe the SS +-tree, a tree structure for supporting similarity searches in a high-dimensional Euclidean space. Compared to the SS-tree, the tree uses a tighter bounding sphere for each node which is an approximation to the smallest enclosing sphere and it also makes a better use of the clustering property of the available data by using(More)
While the conversion from mild cognitive impairment to Alzheimer's disease has received much recent attention, the transition from normal cognition to mild cognitive impairment is largely unexplored. The present pattern recognition study addressed this by using neuropsychological test scores and neuroimaging morphological measures to predict the later(More)