Ye Pan

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This paper addresses the problem of classifying users with different visual abilities based on their pupillary response data while performing computer-based tasks. Multiscale Schur Monotone (MSM) summaries of high frequency pupil diameter measurements are utilized as feature vectors (or input vectors) in this classification. Various MSM measures, such as(More)
Line segment detection is widely used in image process and recognition field. Conventional Hough Transform (CHT) is one of the popular techniques to detect lines accurately. Randomized Hough Transform (RHT) decreases the huge computation of CHT, but the random samples produce large invalid samples, so it increases the time and space complexities. Another(More)
This paper proposes a method of acoustic vehicle classification. We extract acoustic feature of wheeled vehicle and track vehicle based on the optimum wavelet packet energy and classify these two types of vehicle based on the fuzzy classifier. For evaluation purposes, real data are used from DARPA's SensIT project. The experiment results show that the(More)
Local features extraction is one of the most important image processing algorithms, which can be widely used in object recognition, image registration, tracking, etc. To extract key points of an image, SIFT (Scale Invariant Feature Transform) is scale invariant and SURF (Speeded Up Robust Features) is more than three times faster than SIFT. But neither of(More)
We present a novel three-dimensional (3D) face matching approach in this paper. First, 3D facial scans are segmented and four feature points of each face are detected for rough alignment the by Absolute Orientation method. Then a modified Iterative Closest Point (ICP) algorithm is employed for range image registration. A Simulated Annealing (SA) based(More)
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