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    • 1. 发明授权
    • Depth detection method and system using thereof
    • 深度检测方法及其系统使用
    • US08525879B2
    • 2013-09-03
    • US12842277
    • 2010-07-23
    • Chih-Pin LiaoYao-Yang TsaiJay HuangKo-Shyang Wang
    • Chih-Pin LiaoYao-Yang TsaiJay HuangKo-Shyang Wang
    • H04N7/18
    • H04N7/181
    • A depth detection method includes the following steps. First, first and second video data are shot. Next, the first and second video data are compared to obtain initial similarity data including r×c×d initial similarity elements, wherein r, c and d are natural numbers greater than 1. Then, an accumulation operation is performed, with each similarity element serving as a center, according to a reference mask to obtain an iteration parameter. Next, n times of iteration update operations are performed on the initial similarity data according to the iteration parameter to generate updated similarity data. Then, it is judged whether the updated similarity data satisfy a character verification condition. If yes, the updated similarity data is converted into depth distribution data.
    • 深度检测方法包括以下步骤。 首先,拍摄第一和第二视频数据。 接下来,比较第一和第二视频数据以获得包括r×c×d个初始相似度元素的初始相似度数据,其中r,c和d是大于1的自然数。然后,执行累加操作,其中每个相似性元素 作为中心,根据参考掩码获取迭代参数。 接下来,根据迭代参数对初始相似度数据执行n次迭代更新操作,以生成更新的相似度数据。 然后,判断更新的相似度数据是否满足字符验证条件。 如果是,则更新的相似度数据被转换成深度分布数据。
    • 2. 发明申请
    • GESTURE DETECTING METHOD, GESTURE DETECTING SYSTEM AND COMPUTER READABLE STORAGE MEDIUM
    • GESTURE检测方法,检测系统和计算机可读存储介质
    • US20130141326A1
    • 2013-06-06
    • US13600239
    • 2012-08-31
    • Pin-Hong LiouChih-Pin Liao
    • Pin-Hong LiouChih-Pin Liao
    • G06F3/033
    • G06F3/017G06F3/038G06F3/0416
    • A gesture detecting method includes steps of defining an initial reference point in a screen of an electronic device; dividing the screen into N areas radially according to the initial reference point; when a gesture corresponding object moves in the screen and a trajectory of the gesture corresponding object crosses M of the N areas, selecting a sample point from each of the M areas so as to obtain M sample points; and calculating a center and a radius of the trajectory of the gesture corresponding object according to P of the M sample points so as to determine a circular or curved trajectory input. Accordingly, the invention is capable of providing a center, a radius, a direction and an arc angle corresponding to a gesture in real-time without establishing a gesture model.
    • 手势检测方法包括以下步骤:在电子设备的屏幕中定义初始参考点; 根据初始参考点将屏幕径向分为N个区域; 当手势相应对象在屏幕中移动并且手势对应对象的轨迹与N个区域相交时,从M个区域中选择一个采样点,以获得M个采样点; 以及根据所述M个采样点的P计算所述手势对应对象的轨迹的中心和半径,以便确定圆弧或曲线轨迹输入。 因此,本发明能够实时地提供与手势相对应的中心,半径,方向和弧角,而不建立手势模型。
    • 5. 发明申请
    • Depth Detection Method and System Using Thereof
    • 深度检测方法及其使用的系统
    • US20110141274A1
    • 2011-06-16
    • US12842277
    • 2010-07-23
    • Chih-Pin LiaoYao-Yang TsaiJay HuangKo-Shyang Wang
    • Chih-Pin LiaoYao-Yang TsaiJay HuangKo-Shyang Wang
    • H04N7/18
    • H04N7/181
    • A depth detection method includes the following steps. First, first and second video data are shot. Next, the first and second video data are compared to obtain initial similarity data including r×c×d initial similarity elements, wherein r, c and d are natural numbers greater than 1. Then, an accumulation operation is performed, with each similarity element serving as a center, according to a reference mask to obtain an iteration parameter. Next, n times of iteration update operations are performed on the initial similarity data according to the iteration parameter to generate updated similarity data. Then, it is judged whether the updated similarity data satisfy a character verification condition. If yes, the updated similarity data is converted into depth distribution data.
    • 深度检测方法包括以下步骤。 首先,拍摄第一和第二视频数据。 接下来,比较第一和第二视频数据以获得包括r×c×d个初始相似度元素的初始相似度数据,其中r,c和d是大于1的自然数。然后,执行累加操作,其中每个相似性元素 作为中心,根据参考掩码获取迭代参数。 接下来,根据迭代参数对初始相似度数据执行n次迭代更新操作,以生成更新的相似度数据。 然后,判断更新的相似度数据是否满足字符验证条件。 如果是,则更新的相似度数据被转换成深度分布数据。