Parallel triangulation of a polygon in two calls to the trapezoidal map

We give a parallel method for triangulating a simple polygon by two (parallel) calls to the trapezoidal map computation. The method is simpler and more elegant than previous methods. Along the way we obtain an interesting partition of one-sided monotone polygons. Using the best-known trapezoidal map algorithm, ours run in timeO(logn) usingO(n) CREW PRAM processors.This research was supported by NSF Grants No. DCR-84-01898 and No. DCR-84-01633, and ONR Contract N00014-85-K-0046.     

Visibility between two edges of a simple polygon

One of the most recurring themes in many computer applications such as graphics automated cartography, image processing and robotics is the notion of visibility. We are concerned with the visibility between two edges of a simplen-vertex polygon. Four natural definitions of edge-to-edge visibility are proposed. There existO(nlogn) algorithms and complicatedO(nlog logn) algorithms to solve this problem partially and indirectly. A linear running time, and thus optimal algorithm is presented to determine edge-to-edge visibility under any of the four definitions. This simple, efficient, and direct algorithm without computing the triangulation of the simple polygon also identifies the visibility region if it exists.     

A flexible sequence alignment approach on pattern mining and matching for human activity recognition

This paper proposes a flexible sequence alignment approach for pattern mining and matching in the recognition of human activities. During pattern mining, the proposed sequence alignment algorithm is invoked to extract out the representative patterns which denote specific activities of a person from the training patterns. It features high performance and robustness on pattern diversity. Besides, the algorithm evaluates the appearance probability of each pattern as weight and allows adapting pattern length to various human activities. Both of them are able to improve the accuracy of activity recognition. In pattern matching, the proposed algorithm adopts a dynamic programming based strategy to evaluate the correlation degree between each representative activity pattern and the observed activity sequence. It can avoid the trouble on segmenting the observed sequence. Moreover, we are able to obtain recognition results continuously. Besides, the proposed matching algorithm favors recognition of concurrent human activities with parallel matching. The experimental result confirms the high accuracy of human activity recognition by the proposed approach.     

一种基于特征匹配的人脸配准判断方法

现有的人脸识别应用系统大都忽略了人脸配准的检查,造成"误配准灾难",导致识别性能下降。因此,对规格化后的人脸图像进行判断筛选,以保证只有正确配准的人脸图像才能用于后续识别。选用一定数量正确配准的规格化人脸图像平均值作为标准人脸,用SIFT关键点定位方法得到标准人脸的多个关键点,采用分块的梯度方向直方图统计方法提取关键点的邻域图像特征;然后,将标准人脸的关键点位置作为待检测人脸的定位点,用同样的方法提取定位点的邻域图像特征;计算待检图像与标准人脸图像对应关键点的特征矢量相似度,设定合理阈值判断待检测图像是否配准。实验证明,该方法能有效去除误配准人脸图像,有利于提高人脸识别系统的可靠性。     

Control of the pretilt angle for liquid crystal alignment using novel electrospray deposition methods with two capillaries

The electrospray deposition (ESD) method is an established film‐forming technique. To control the pretilt angle on films, we developed two novel ESD methods for spraying two kinds of solutions containing alignment materials. One method is a simultaneous spraying method, while the other is a time‐divided spraying method. When we used the simultaneous‐spraying ESD method, we observed numerous fine liquid crystal (LC) domains with a diameter of approximately 10 µm in the LC cell. These LC domains were substantially smaller than those of LCs fabricated using the conventional ESD method. However, the pretilt angle could not be controlled over a wide range because multiple parameters could not be simultaneously controlled to achieve a stable spray. Using the time‐division ESD method, we controlled the pretilt angle over a wide range from 5° to 40°, with tiny domains. As a demonstration, we fabricated a 270° super‐twisted nematic mode cell using this method.