Dalong Li

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Plan-view projection of real-time depth imagery can improve the statistics of its intrinsic 3D data, and allows for cleaner separation of occluding and closely-interacting people. We build a probabilistic, real-time multi-person tracking system upon a plan-view image substrate that well preserves both shape and size information of foreground objects. The(More)
In this paper, we describe an algorithm for identifying a parametrically described blur based on kurtosis minimization. Using different choices for the parameters of the blur, the noisy blurred image is restored using Wiener filter. We use the kurtosis as a measurement of the quality of the restored image. From the set of the candidate deblurred images ,(More)
In this paper, an example-based image denoising algorithm is introduced. Image denoising is formulated as a regression problem, which is then solved using support vector regression (SVR). Using noisy images as training sets, SVR models are developed. The models can then be used to denoise different images corrupted by random noise at different levels.(More)
Since abnormal control chart patterns (CCPs) are indicators of production processes being out-of-control, it is a critical task to recognize these patterns effectively based on process measurements. Most methods on CCP recognition assume that the process data only suffers from single type of unnatural pattern. In reality, the observed process data could be(More)
Atmospheric turbulence is caused by the random fluctuations of the refraction index of the medium. It can lead to blurring in images acquired from a long distance away. Since the degradation is often not completely known, the problem is viewed as blind image deconvolution or blur identification. Our previous work has observed that blurring increases(More)
This paper describes an algorithm for the restoration of a noisy blurred image based on support vector regression. The blind image deconvolution was formulated as a machine learning problem. From the training set, the mapping between the noisy blurred image and the original image are learned by support vector regression (SVR). With the acquired mapping, the(More)
The presence of optical turbulence in video acquired by cameras viewing scenes at long distances can contribute significantly to degradation. This problem arises routinely, for example , in astronomy where objects of interest reside beyond the earth's atmosphere. Optical turbulence introduces time-varying perturbations in the images as well as blurring. In(More)