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Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on the alignment of nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods...
We present a histogram-based real-time solution to detecting directly irradiated regions in digital fluoroscopic images. Our method leverages the power of model matching, machine learning and domain knowledge to characterize and segment images using histograms. The input image is automatically identified as containing partial, all, or null direct radiation. The regions with direct radiation are segmented...
This letter presents an approach for automatically estimating the spatial bound of the blur kernel in a motion-blurred image based on the statistics of multilevel image gradients. We observe that blur has a significant impact on the histogram of oriented gradients (HOGs) at higher levels of an image pyramid, but has much less of an impact at coarser levels. Based on this fact, we estimate the spatial...
The standard support vector machine (SVM) is celebrated for its theoretically guaranteed generalization performance. However, it lacks sparsity and thus cannot be used for feature selection. Zero norm SVM is ideal in the sense of sparsity while its optimization is prohibitive due to the combinatorial nature of zero norm. In this paper, 1 norm and infinite norm constraints are employed simultaneously...
Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper we have developed a novel body sensor network based recognition system to identify the specific gait pattern of Parkinson's disease (PD). Firstly, a BSN with 16 nodes is used to acquire...
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