This article presents a robotic visual system that allows effective recognition of multiple-angle hand gestures in finger guessing games. We shot images of hand gestures at various angles to train support vector machine (SVM) for the construction of a multiple-angle hand gesture recognition system. Our experimental results show that the hand gesture recognition system presented by this article can effectively recognize hand gestures, at over 95%, of different angles and sizes, with different ornaments, and of different skin colors, while recognizing right or left hand gestures, at up to 90% recognition rate.I.
Given two sequences S 1 , S 2 , and a constrained sequence C, a longest common subsequence of S 1 , S 2 with restriction to C is called a constrained longest common subsequence of S 1 and S 2 with C. At the same time, an optimal alignment of S 1 , S 2 with restriction to C is called a constrained pairwise sequence alignment of S 1 and S 2 with C. Previous algorithms have shown that the constrained longest common subsequence problem is a special case of the constrained pairwise sequence alignment problem, and that both of them can be solved in O(rnm) time, where r, n, and m represent the lengths of C, S 1 , and S 2 , respectively. In this paper, we extend the definition of constrained pairwise sequence alignment to a more flexible version, called weighted constrained pairwise sequence alignment, in which some constraints might be ignored. We first give an O(rnm)-time algorithm for solving the weighted constrained pairwise sequence alignment problem, then show that our extension can be adopted to solve some constraint-related problems that cannot be solved by previous algorithms for the constrained longest common subsequence problem or the constrained pairwise sequence alignment problem. Therefore, in contrast to previous results, our extension is a new and suitable model for sequence analysis.
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