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    • 4. 发明申请
    • SEMANTIC PARSING OF OBJECTS IN VIDEO
    • 视频中的对象语义分离
    • US20120027304A1
    • 2012-02-02
    • US12845095
    • 2010-07-28
    • Lisa Marie BrownRogerio Schmidt FerisArun HampapurDaniel André Vaquero
    • Lisa Marie BrownRogerio Schmidt FerisArun HampapurDaniel André Vaquero
    • G06K9/46
    • G06K9/00718G06K9/00369G06K9/00664G06K9/469G06K9/6201G06K9/6202G06K9/6232G06K9/6857
    • The invention provides an improved method to detect semantic attributes of human body in computer vision. In detecting semantic attributes of human body in computer vision, the invention maintains a list of semantic attributes, each of which corresponds to a human body part. A computer module then analyzes segments of a frame of a digital video to detect each semantic attribute by finding a most likely attribute for each segment. A threshold is applied to select candidate segments of the frame for further analysis. The candidate segments of the frame then go through geometric and resolution context analysis by applying the physical structure principles of a human body and by analyzing increasingly higher resolution versions of the image to verify the existence and accuracy of parts and attributes. A computer module computes a resolution context score for a lower resolution version of the image based on a weighted average score computed for a higher resolution version of the image by evaluating appearance features, geometric features, and resolution context features when available on the higher resolution version of the image. Finally, an optimal configuration step is performed via dynamic programming to select an optimal output with both semantic attributes and spatial positions of human body parts on the frame.
    • 本发明提供了一种用于检测计算机视觉中人体语义属性的改进方法。 在检测计算机视觉中人体的语义属性时,本发明保留了语义属性的列表,每个语义属性对应于人体部分。 然后,计算机模块通过为每个段找到最可能的属性来分析数字视频的帧的段以检测每个语义属性。 应用阈值来选择帧的候选片段用于进一步分析。 然后,帧的候选片段通过应用人体的物理结构原理并通过分析图像的越来越高的分辨率版本来验证部件和属性的存在和准确性来进行几何和分辨率上下文分析。 计算机模块基于通过在更高分辨率版本上可用时评估外观特征,几何特征和分辨率上下文特征来计算针对图像的较高分辨率版本的加权平均得分,来计算图像的较低分辨率版本的分辨率上下文得分 的图像。 最后,通过动态规划执行最佳配置步骤,以选择具有框架上人体部位的语义属性和空间位置的最优输出。
    • 7. 发明申请
    • DETECTION OF ABANDONED AND REMOVED OBJECTS IN A VIDEO STREAM
    • 在视频流中检测丢弃和删除的对象
    • US20090238462A1
    • 2009-09-24
    • US12053827
    • 2008-03-24
    • Rogerio Schmidt FerisArun HampapurZuoxuan Max LuYing-li Tian
    • Rogerio Schmidt FerisArun HampapurZuoxuan Max LuYing-li Tian
    • G06K9/46
    • G06K9/00771G06K9/44G06T7/254G06T2207/10016G06T2207/30112
    • A method for processing a time-ordered sequence of video frames. The method is implemented by execution of program code on a processor of a computer system. Each frame includes a two-dimensional array of pixels and a frame-dependent color intensity at each pixel. A current frame and at least one frame occurring prior to the current frame in the sequence are analyzed via a background subtraction on the at least one frame to determine a background image and a static region mask associated with a static region. The background subtraction determines an existence of a static object relating to the static region. A status of the static object is determined, the status being either that the static object is an abandoned object or that the static object is a removed object. The determined status is stored in a data storage medium of the computer system.
    • 一种用于处理视频帧的时间有序序列的方法。 该方法通过在计算机系统的处理器上执行程序代码来实现。 每个帧包括像素的二维阵列和每个像素处的依赖于帧的颜色强度。 通过在至少一个帧上的背景减法来分析在序列中的当前帧之前出现的当前帧和至少一个帧,以确定与静态区域相关联的背景图像和静态区域掩模。 背景减法确定与静态区域相关的静态对象的存在。 确定静态对象的状态,状态是静态对象是被放弃的对象,或者静态对象是被删除的对象。 所确定的状态存储在计算机系统的数据存储介质中。